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  1. .ipynb_checkpoints/Untitled-checkpoint.ipynb +6 -0
  2. .ipynb_checkpoints/requirements-checkpoint.txt +20 -0
  3. .ipynb_checkpoints/run-checkpoint.py +127 -0
  4. .ipynb_checkpoints/tableQA_single_table-checkpoint.py +1295 -0
  5. JointBERT-master/.gitignore +114 -0
  6. JointBERT-master/LICENSE +201 -0
  7. JointBERT-master/README.md +96 -0
  8. JointBERT-master/__pycache__/data_loader.cpython-37.pyc +0 -0
  9. JointBERT-master/__pycache__/data_loader.cpython-38.pyc +0 -0
  10. JointBERT-master/__pycache__/main.cpython-37.pyc +0 -0
  11. JointBERT-master/__pycache__/main.cpython-38.pyc +0 -0
  12. JointBERT-master/__pycache__/predict.cpython-37.pyc +0 -0
  13. JointBERT-master/__pycache__/predict.cpython-38.pyc +0 -0
  14. JointBERT-master/__pycache__/trainer.cpython-37.pyc +0 -0
  15. JointBERT-master/__pycache__/trainer.cpython-38.pyc +0 -0
  16. JointBERT-master/__pycache__/utils.cpython-37.pyc +0 -0
  17. JointBERT-master/__pycache__/utils.cpython-38.pyc +0 -0
  18. JointBERT-master/data/atis/dev/label +500 -0
  19. JointBERT-master/data/atis/dev/seq.in +500 -0
  20. JointBERT-master/data/atis/dev/seq.out +500 -0
  21. JointBERT-master/data/atis/intent_label.txt +22 -0
  22. JointBERT-master/data/atis/slot_label.txt +122 -0
  23. JointBERT-master/data/atis/test/label +893 -0
  24. JointBERT-master/data/atis/test/seq.in +893 -0
  25. JointBERT-master/data/atis/test/seq.out +893 -0
  26. JointBERT-master/data/atis/train/label +4478 -0
  27. JointBERT-master/data/atis/train/seq.in +0 -0
  28. JointBERT-master/data/atis/train/seq.out +0 -0
  29. JointBERT-master/data/snips/dev/label +700 -0
  30. JointBERT-master/data/snips/dev/seq.in +700 -0
  31. JointBERT-master/data/snips/dev/seq.out +700 -0
  32. JointBERT-master/data/snips/intent_label.txt +8 -0
  33. JointBERT-master/data/snips/slot_label.txt +74 -0
  34. JointBERT-master/data/snips/test/label +700 -0
  35. JointBERT-master/data/snips/test/seq.in +700 -0
  36. JointBERT-master/data/snips/test/seq.out +700 -0
  37. JointBERT-master/data/snips/train/label +0 -0
  38. JointBERT-master/data/snips/train/seq.in +0 -0
  39. JointBERT-master/data/snips/train/seq.out +0 -0
  40. JointBERT-master/data/vocab_process.py +48 -0
  41. JointBERT-master/data_loader.py +255 -0
  42. JointBERT-master/main.py +72 -0
  43. JointBERT-master/model/__init__.py +3 -0
  44. JointBERT-master/model/__pycache__/__init__.cpython-37.pyc +0 -0
  45. JointBERT-master/model/__pycache__/__init__.cpython-38.pyc +0 -0
  46. JointBERT-master/model/__pycache__/modeling_jointalbert.cpython-37.pyc +0 -0
  47. JointBERT-master/model/__pycache__/modeling_jointalbert.cpython-38.pyc +0 -0
  48. JointBERT-master/model/__pycache__/modeling_jointbert.cpython-37.pyc +0 -0
  49. JointBERT-master/model/__pycache__/modeling_jointbert.cpython-38.pyc +0 -0
  50. JointBERT-master/model/__pycache__/modeling_jointdistilbert.cpython-37.pyc +0 -0
.ipynb_checkpoints/Untitled-checkpoint.ipynb ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ {
2
+ "cells": [],
3
+ "metadata": {},
4
+ "nbformat": 4,
5
+ "nbformat_minor": 5
6
+ }
.ipynb_checkpoints/requirements-checkpoint.txt ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ torch==1.6.0
2
+ #dask[dataframe]
3
+ #dask[distributed]
4
+ #keybert
5
+ #bertopic
6
+ jieba
7
+ seaborn
8
+ sqlite_utils
9
+ sqlitefts
10
+ icecream
11
+ protobuf
12
+ #snorkel
13
+ pyarrow
14
+ transformers==3.0.2
15
+ seqeval==0.0.12
16
+ pytorch-crf==0.7.2
17
+ rank_bm25
18
+ nltk
19
+ gradio
20
+
.ipynb_checkpoints/run-checkpoint.py ADDED
@@ -0,0 +1,127 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from tableQA_single_table import *
2
+
3
+ import json
4
+ import os
5
+ import sys
6
+
7
+ def run_sql_query(s, df):
8
+ conn = sqlite3.connect(":memory:")
9
+
10
+ assert isinstance(df, pd.DataFrame)
11
+ question_column = s.question_column
12
+ if question_column is None:
13
+ return {
14
+ "sql_query": "",
15
+ "cnt_num": 0,
16
+ "conclusion": []
17
+ }
18
+ total_conds_filtered = s.total_conds_filtered
19
+ agg_pred = s.agg_pred
20
+ conn_pred = s.conn_pred
21
+ sql_format = "SELECT {} FROM {} {}"
22
+ header = df.columns.tolist()
23
+ if len(header) > len(set(header)):
24
+ req = []
25
+ have_req = set([])
26
+ idx = 0
27
+ for h in header:
28
+ if h in have_req:
29
+ idx += 1
30
+ req.append("{}_{}".format(h, idx))
31
+ else:
32
+ req.append(h)
33
+ have_req.add(h)
34
+ header = req
35
+ def format_right(val):
36
+ val = str(val)
37
+ is_string = True
38
+ try:
39
+ literal_eval(val)
40
+ is_string = False
41
+ except:
42
+ pass
43
+ if is_string:
44
+ return "'{}'".format(val)
45
+ else:
46
+ return val
47
+ #ic(question_column, header)
48
+ assert question_column in header
49
+ assert all(map(lambda t3: t3[0] in header, total_conds_filtered))
50
+ assert len(header) == len(set(header))
51
+ index_header_mapping = dict(enumerate(header))
52
+ header_index_mapping = dict(map(lambda t2: (t2[1], t2[0]) ,index_header_mapping.items()))
53
+ assert len(index_header_mapping) == len(header_index_mapping)
54
+ df_saved = df.copy()
55
+ df_saved.columns = list(map(lambda idx: "col_{}".format(idx), range(len(header))))
56
+ df_saved.to_sql("Mem_Table", conn, if_exists = "replace", index = False)
57
+ question_column_idx = header.index(question_column)
58
+ sql_question_column = "col_{}".format(question_column_idx)
59
+ sql_total_conds_filtered = list(map(lambda t3: ("col_{}".format(header.index(t3[0])), t3[1], format_right(t3[2])), total_conds_filtered))
60
+ sql_agg_pred = agg_pred
61
+ if sql_agg_pred.strip():
62
+ sql_agg_pred = "{}()".format(sql_agg_pred)
63
+ else:
64
+ sql_agg_pred = "()"
65
+ sql_agg_pred = sql_agg_pred.replace("()", "({})")
66
+ sql_conn_pred = conn_pred
67
+ if sql_conn_pred.strip():
68
+ pass
69
+ else:
70
+ sql_conn_pred = ""
71
+ #sql_where_string = "" if not (sql_total_conds_filtered and sql_conn_pred) else "WHERE {}".format(" {} ".format(sql_conn_pred).join(map(lambda t3: "{} {} {}".format(t3[0],"=" if t3[1] == "==" else t3[1], t3[2]), sql_total_conds_filtered)))
72
+ sql_where_string = "" if not (sql_total_conds_filtered) else "WHERE {}".format(" {} ".format(sql_conn_pred if sql_conn_pred else "and").join(map(lambda t3: "{} {} {}".format(t3[0],"=" if t3[1] == "==" else t3[1], t3[2]), sql_total_conds_filtered)))
73
+ #ic(sql_total_conds_filtered, sql_conn_pred, sql_where_string, s)
74
+ sql_query = sql_format.format(sql_agg_pred.format(sql_question_column), "Mem_Table", sql_where_string)
75
+ cnt_sql_query = sql_format.format("COUNT(*)", "Mem_Table", sql_where_string).strip()
76
+ #ic(cnt_sql_query)
77
+ cnt_num = pd.read_sql(cnt_sql_query, conn).values.reshape((-1,))[0]
78
+ if cnt_num == 0:
79
+ return {
80
+ "sql_query": sql_query,
81
+ "cnt_num": 0,
82
+ "conclusion": []
83
+ }
84
+ query_conclusion_list = pd.read_sql(sql_query, conn).values.reshape((-1,)).tolist()
85
+ return {
86
+ "sql_query": sql_query,
87
+ "cnt_num": cnt_num,
88
+ "conclusion": query_conclusion_list
89
+ }
90
+
91
+ #save_conn = sqlite3.connect(":memory:")
92
+ def single_table_pred(question, pd_df):
93
+ assert type(question) == type("")
94
+ assert isinstance(pd_df, pd.DataFrame)
95
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
96
+
97
+ #print("pd_df :")
98
+ #print(pd_df)
99
+
100
+ tableqa_df = full_before_cat_decomp(pd_df, qs_df, only_req_columns=False)
101
+
102
+ #print("tableqa_df :")
103
+ #print(tableqa_df)
104
+
105
+ assert tableqa_df.shape[0] == 1
106
+ #sql_query_dict = run_sql_query(tableqa_df.iloc[0], pd_df, save_conn)
107
+ sql_query_dict = run_sql_query(tableqa_df.iloc[0], pd_df)
108
+ return sql_query_dict
109
+
110
+
111
+ if __name__ == "__main__":
112
+ szse_summary_df = pd.read_csv(os.path.join(main_path ,"data/df1.csv"))
113
+ data = {
114
+ "tqa_question": "EPS大于0且周涨跌大于5的平均市值是多少?",
115
+ "tqa_header": szse_summary_df.columns.tolist(),
116
+ "tqa_rows": szse_summary_df.values.tolist(),
117
+ "tqa_data_path": os.path.join(main_path ,"data/df1.csv"),
118
+ "tqa_answer": {
119
+ "sql_query": "SELECT AVG(col_4) FROM Mem_Table WHERE col_5 > 0 and col_3 > 5",
120
+ "cnt_num": 2,
121
+ "conclusion": [57.645]
122
+ }
123
+ }
124
+
125
+ pd_df = pd.DataFrame(data["tqa_rows"], columns = data["tqa_header"])
126
+ question = data["tqa_question"]
127
+ single_table_pred(question, pd_df)
.ipynb_checkpoints/tableQA_single_table-checkpoint.py ADDED
@@ -0,0 +1,1295 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/usr/bin/env python
2
+ # coding: utf-8
3
+ #### env base_cp
4
+
5
+ #main_path = "/Users/svjack/temp/gradio_prj/tableQA-Chinese-main"
6
+ #main_path = "/User/tableQA-Chinese-main"
7
+ #main_path = "/temp/tableQA-Chinese-main"
8
+ main_path = "."
9
+
10
+ import pandas as pd
11
+ import numpy as np
12
+ import os
13
+ import ast
14
+ import re
15
+ import json
16
+ from icecream import ic
17
+ from copy import deepcopy
18
+ from itertools import product, combinations
19
+
20
+
21
+ import pandas as pd
22
+ import os
23
+ import sys
24
+ from pyarrow.filesystem import LocalFileSystem
25
+ from functools import reduce
26
+ import nltk
27
+ from nltk import pos_tag, word_tokenize
28
+ from collections import namedtuple
29
+ from ast import literal_eval
30
+
31
+ from torch.nn import functional
32
+ import numpy as np
33
+ import torch
34
+ from torch import nn
35
+ from torch.nn import init
36
+ from torch.nn.utils import rnn as rnn_utils
37
+ import math
38
+
39
+ from icecream import ic
40
+ import seaborn as sns
41
+
42
+ import matplotlib.pyplot as plt
43
+
44
+ import shutil
45
+
46
+ #from keybert import KeyBERT
47
+ #from bertopic import BERTopic
48
+
49
+
50
+ import sqlite3
51
+ import sqlite_utils
52
+ from icecream import ic
53
+ import jieba
54
+ import pandas as pd
55
+ import urllib.request
56
+ from urllib.parse import quote
57
+ from time import sleep
58
+ import json
59
+ import os
60
+ from collections import defaultdict
61
+ import re
62
+ from functools import reduce, partial
63
+
64
+ #### used in this condition extract in training.
65
+ op_sql_dict = {0:">", 1:"<", 2:"==", 3:"!="}
66
+ #### used by clf for intension inference
67
+ agg_sql_dict = {0:"", 1:"AVG", 2:"MAX", 3:"MIN", 4:"COUNT", 5:"SUM"}
68
+ #### final to combine them (one for 0, and multi for 1 2)
69
+ conn_sql_dict = {0:"", 1:"and", 2:"or"}
70
+
71
+ #### kws and time pattern defination
72
+ and_kws = ("且", "而且", "并且", "和", "当中", "同时")
73
+ or_kws = ("或", "或者",)
74
+ conn_kws = and_kws + or_kws
75
+
76
+ pattern_list = [u"[年月\.\-\d]+", u"[年月\d]+", u"[年个月\d]+", u"[年月日\d]+"]
77
+
78
+ time_kws = ("什么时候", "时间", "时候")
79
+
80
+ sum_count_high_kws = ('多少个', '有几个', '总共') + ('总和','一共',) + ("总数",)
81
+ mean_kws = ('平均数', '均值', '平均值', '平均')
82
+ max_kws = ('最大', '最多', '最大值', '最高')
83
+ min_kws = ('最少', '最小值', '最小', '最低')
84
+ sum_count_low_kws = ('个', '总共') + ('总和','加','总','一共','和',) + ("哪些", "查", "数量", "数") + ("几",) + ('多少', "多大") + ("总数",)
85
+ max_special_kws = ("以上", "大于")
86
+ min_special_kws = ("以下", "小于")
87
+
88
+ qst_kws = ("多少", "什么", "多大", "哪些", "怎么", "情况", "那些", "哪个")
89
+
90
+ only_kws_columns = {"城市": "=="}
91
+
92
+ ##### jointbert predict model init start
93
+ #jointbert_path = "../../featurize/JointBERT"
94
+ #jointbert_path = "/Users/svjack/temp/gradio_prj/tableQA-Chinese-main/JointBERT-master"
95
+ jointbert_path = os.path.join(main_path, "JointBERT-master")
96
+ sys.path.append(jointbert_path)
97
+
98
+
99
+ from model.modeling_jointbert import JointBERT
100
+ from model.modeling_jointbert import *
101
+ from trainer import *
102
+ from main import *
103
+ from data_loader import *
104
+
105
+
106
+ pred_parser = argparse.ArgumentParser()
107
+
108
+ pred_parser.add_argument("--input_file", default="conds_pred/seq.in", type=str, help="Input file for prediction")
109
+ pred_parser.add_argument("--output_file", default="conds_pred/sample_pred_out.txt", type=str, help="Output file for prediction")
110
+ #pred_parser.add_argument("--model_dir", default="bert", type=str, help="Path to save, load model")
111
+ pred_parser.add_argument("--model_dir", default= os.path.join(main_path ,"data/bert"), type=str, help="Path to save, load model")
112
+ #pred_parser.add_argument("--model_dir", default= os.path.join(main_path ,"JBert_Zh_Condition_Extractor"), type=str, help="Path to save, load model")
113
+
114
+
115
+ pred_parser.add_argument("--batch_size", default=32, type=int, help="Batch size for prediction")
116
+ pred_parser.add_argument("--no_cuda", action="store_true", help="Avoid using CUDA when available")
117
+
118
+
119
+ pred_parser_config_dict = dict(map(lambda item:(item.option_strings[0].replace("--", ""), item.default) ,pred_parser.__dict__["_actions"]))
120
+ pred_parser_config_dict = dict(filter(lambda t2: t2[0] != "-h", pred_parser_config_dict.items()))
121
+
122
+ pred_parser_namedtuple = namedtuple("pred_parser_config", pred_parser_config_dict.keys())
123
+ for k, v in pred_parser_config_dict.items():
124
+ if type(v) == type(""):
125
+ exec("pred_parser_namedtuple.{}='{}'".format(k, v))
126
+ else:
127
+ exec("pred_parser_namedtuple.{}={}".format(k, v))
128
+
129
+
130
+ from predict import *
131
+
132
+
133
+ pred_config = pred_parser_namedtuple
134
+ args = get_args(pred_config)
135
+ device = get_device(pred_config)
136
+
137
+ args_parser_namedtuple = namedtuple("args_config", args.keys())
138
+ for k, v in args.items():
139
+ if type(v) == type(""):
140
+ exec("args_parser_namedtuple.{}='{}'".format(k, v))
141
+ else:
142
+ exec("args_parser_namedtuple.{}={}".format(k, v))
143
+
144
+
145
+ args = args_parser_namedtuple
146
+
147
+ #args.data_dir = "/Users/svjack/temp/gradio_prj/tableQA-Chinese-main/data"
148
+ args.data_dir = os.path.join(main_path, "data")
149
+
150
+ '''
151
+ pred_model = MODEL_CLASSES["bert"][1].from_pretrained(args.model_dir,
152
+ args=args,
153
+ intent_label_lst=get_intent_labels(args),
154
+ slot_label_lst=get_slot_labels(args))
155
+ '''
156
+ pred_model = MODEL_CLASSES["bert"][1].from_pretrained(
157
+ os.path.join(main_path, "data/bert")
158
+ ,
159
+ args=args,
160
+ intent_label_lst=get_intent_labels(args),
161
+ slot_label_lst=get_slot_labels(args))
162
+
163
+ pred_model.to(device)
164
+ pred_model.eval()
165
+
166
+ intent_label_lst = get_intent_labels(args)
167
+ slot_label_lst = get_slot_labels(args)
168
+ pad_token_label_id = args.ignore_index
169
+ tokenizer = load_tokenizer(args)
170
+ ## jointbert predict model init end
171
+
172
+
173
+ ###### one sent conds decomp start
174
+ def predict_single_sent(question):
175
+ text = " ".join(list(question))
176
+ batch = convert_input_file_to_tensor_dataset([text.split(" ")], pred_config, args, tokenizer, pad_token_label_id).tensors
177
+ batch = tuple(t.to(device) for t in batch)
178
+ inputs = {"input_ids": batch[0],
179
+ "attention_mask": batch[1],
180
+ "intent_label_ids": None,
181
+ "slot_labels_ids": None}
182
+ inputs["token_type_ids"] = batch[2]
183
+ outputs = pred_model(**inputs)
184
+ _, (intent_logits, slot_logits) = outputs[:2]
185
+ intent_preds = intent_logits.detach().cpu().numpy()
186
+ slot_preds = slot_logits.detach().cpu().numpy()
187
+ intent_preds = np.argmax(intent_preds, axis=1)
188
+ slot_preds = np.argmax(slot_preds, axis=2)
189
+ all_slot_label_mask = batch[3].detach().cpu().numpy()
190
+ slot_label_map = {i: label for i, label in enumerate(slot_label_lst)}
191
+ slot_preds_list = [[] for _ in range(slot_preds.shape[0])]
192
+ for i in range(slot_preds.shape[0]):
193
+ for j in range(slot_preds.shape[1]):
194
+ if all_slot_label_mask[i, j] != pad_token_label_id:
195
+ slot_preds_list[i].append(slot_label_map[slot_preds[i][j]])
196
+ pred_l = []
197
+ for words, slot_preds, intent_pred in zip([text.split(" ")], slot_preds_list, intent_preds):
198
+ line = ""
199
+ for word, pred in zip(words, slot_preds):
200
+ if pred == 'O':
201
+ line = line + word + " "
202
+ else:
203
+ line = line + "[{}:{}] ".format(word, pred)
204
+ pred_l.append((line, intent_label_lst[intent_pred]))
205
+ return pred_l[0]
206
+
207
+
208
+ ###@@ conn_kws = ["且", "或", "或者", "和"]
209
+ '''
210
+ and_kws = ("且", "而且", "并且", "和", "当中", "同时")
211
+ or_kws = ("或", "或者",)
212
+ conn_kws = and_kws + or_kws
213
+ '''
214
+ #conn_kws = ("且", "或", "或者", "和") + ("而且", "并且", "当中")
215
+ #### some algorithm use in it.
216
+ def recurrent_extract(question):
217
+ def filter_relation(text):
218
+ #kws = ["且", "或", "或者", "和"]
219
+ kws = conn_kws
220
+ req = text
221
+ for kw in sorted(kws, key= lambda x: len(x))[::-1]:
222
+ req = req.replace(kw, "")
223
+ return req
224
+ def produce_plain_text(text):
225
+ ##### replace tag string from text
226
+ kws = ["[", "]", " ", ":B-HEADER", ":I-HEADER", ":B-VALUE", ":I-VALUE"]
227
+ plain_text = text
228
+ for kw in kws:
229
+ plain_text = plain_text.replace(kw, "")
230
+ return plain_text
231
+ def find_min_commmon_strings(c):
232
+ ##### {"jack", "ja", "ss", "sss", "ps", ""} -> {"ja", "ss", "ps"}
233
+ common_strings = list(filter(lambda x: type(x) == type("") ,
234
+ map(lambda t2: t2[0]
235
+ if t2[0] in t2[1]
236
+ else (t2[1]
237
+ if t2[1] in t2[0]
238
+ else (t2[0], t2[1])),combinations(c, 2))))
239
+ req = set([])
240
+ while c:
241
+ ele = c.pop()
242
+ if all(map(lambda cc: cc not in ele, common_strings)):
243
+ req.add(ele)
244
+ req = req.union(set(common_strings))
245
+ return set(filter(lambda x: x, req))
246
+ def extract_scope(scope_text):
247
+ def find_max_in(plain_text ,b_chars, i_chars):
248
+ chars = "".join(b_chars + i_chars)
249
+ while chars and chars not in plain_text:
250
+ chars = chars[:-1]
251
+ return chars
252
+ b_header_chars = re.findall(r"([\w\W]):B-HEADER", scope_text)
253
+ i_header_chars = re.findall(r"([\w\W]):I-HEADER", scope_text)
254
+ b_value_chars = re.findall(r"([\w\W]):B-VALUE", scope_text)
255
+ i_value_chars = re.findall(r"([\w\W]):I-VALUE", scope_text)
256
+ if len(b_header_chars) != 1 or len(b_value_chars) != 1:
257
+ return None
258
+ plain_text = produce_plain_text(scope_text)
259
+ header = find_max_in(plain_text, b_header_chars, i_header_chars)
260
+ value = find_max_in(plain_text, b_value_chars, i_value_chars)
261
+ if (not header) or (not value):
262
+ return None
263
+ return (header, value)
264
+ def find_scope(text):
265
+ start_index = text.find("[")
266
+ end_index = text.rfind("]")
267
+ if start_index == -1 or end_index == -1:
268
+ return text
269
+ scope_text = text[start_index: end_index + 1]
270
+ res_text = filter_relation(text.replace(scope_text, "")).replace(" ", "").strip()
271
+ return (scope_text, res_text)
272
+ def produce_all_attribute_remove(req):
273
+ if not req:
274
+ return None
275
+ string_or_t2 = find_scope(req[-1][0])
276
+ assert type(string_or_t2) in [type(""), type((1,))]
277
+ if type(string_or_t2) == type(""):
278
+ return string_or_t2
279
+ else:
280
+ return string_or_t2[-1]
281
+ def extract_all_attribute(req):
282
+ extract_list = list(map(lambda t2: (t2[0][0], t2[1], t2[0][1]) ,
283
+ filter(lambda x: x[0] ,
284
+ map(lambda tt2_t2: (extract_scope(tt2_t2[0][0]), tt2_t2[1]) ,
285
+ filter(lambda t2_t2: "HEADER" in t2_t2[0][0] and "VALUE" in t2_t2[0][0] ,
286
+ filter(lambda string_or_t2_t2: type(string_or_t2_t2[0]) == type((1,)),
287
+ map(lambda tttt2: (find_scope(tttt2[0]), tttt2[1]),
288
+ req)))))))
289
+ return extract_list
290
+ def extract_attributes_relation_string(plain_text, all_attributes, res):
291
+ if not all_attributes:
292
+ return plain_text.replace(res if res else "", "")
293
+ def replace_by_one_l_r(text ,t3):
294
+ l, _, r = t3
295
+ ##### produce multi l, r to satisfy string contrain problem
296
+ l0, l1 = l, l
297
+ r0, r1 = r, r
298
+ while l0 and l0 not in text:
299
+ l0 = l0[:-1]
300
+ while l1 and l1 not in text:
301
+ l1 = l1[1:]
302
+ while r0 and r0 not in text:
303
+ r0 = r0[:-1]
304
+ while r1 and r1 not in text:
305
+ r1 = r1[1:]
306
+ if not l or not r:
307
+ return text
308
+
309
+ conclusion = set([])
310
+ for l_, r_ in product([l0, l1], [r0, r1]):
311
+ l_r_conclusion = re.findall("({}.*?{})".format(l_, r_), text)
312
+ r_l_conclusion = re.findall("({}.*?{})".format(r_, l_), text)
313
+ conclusion = conclusion.union(set(l_r_conclusion + r_l_conclusion))
314
+
315
+ ##### because use produce multi must choose the shortest elements from them
316
+ ## to prevent "relation word" also be replaced.
317
+ conclusion_filtered = find_min_commmon_strings(conclusion)
318
+
319
+ conclusion = conclusion_filtered
320
+ req_text = text
321
+ for c in conclusion:
322
+ req_text = req_text.replace(c, "")
323
+ return req_text
324
+ req_text_ = plain_text
325
+ for t3 in all_attributes:
326
+ req_text_ = replace_by_one_l_r(req_text_, t3)
327
+ return req_text_.replace(res, "")
328
+ req = []
329
+ t2 = predict_single_sent(question)
330
+ req.append(t2)
331
+ while "[" in t2[0]:
332
+ scope = find_scope(t2[0])
333
+ if type(scope) == type(""):
334
+ break
335
+ else:
336
+ assert type(scope) == type((1,))
337
+ scope_text, res_text = scope
338
+ #ic(req)
339
+ t2 = predict_single_sent(res_text)
340
+ req.append(t2)
341
+ req = list(filter(lambda tt2: "HEADER" in tt2[0] and "VALUE" in tt2[0] , req))
342
+ res = produce_all_attribute_remove(req)
343
+ #ic(req)
344
+ all_attributes = extract_all_attribute(req)
345
+ # plain_text = produce_plain_text(scope_text)
346
+
347
+ return all_attributes, res, extract_attributes_relation_string(produce_plain_text(req[0][0] if req else ""), all_attributes, res)
348
+
349
+
350
+ def rec_more_time(decomp):
351
+ assert type(decomp) == type((1,)) and len(decomp) == 3
352
+ assert not decomp[0]
353
+ res, relation_string = decomp[1:]
354
+ new_decomp = recurrent_extract(relation_string)
355
+ #### stop if rec not help by new_decomp[1] != decomp[1]
356
+ if not new_decomp[0] and new_decomp[1] != decomp[1]:
357
+ return rec_more_time(new_decomp)
358
+ return (new_decomp[0], res, new_decomp[1])
359
+ ### one sent conds decomp end
360
+
361
+
362
+ ##### data source start
363
+ #train_path = "../TableQA/TableQA/train"
364
+ #train_path = "/Users/svjack/temp/gradio_prj/tableQA-Chinese-main/data/TableQA-master/train"
365
+ train_path = os.path.join(main_path, "data/TableQA-master/train")
366
+ def data_loader(table_json_path = os.path.join(train_path ,"train.tables.json"),
367
+ json_path = os.path.join(train_path ,"train.json"),
368
+ req_table_num = 1):
369
+ assert os.path.exists(table_json_path)
370
+ assert os.path.exists(json_path)
371
+ json_df = pd.read_json(json_path, lines = True)
372
+ all_tables = pd.read_json(table_json_path, lines = True)
373
+ if req_table_num is not None:
374
+ assert type(req_table_num) == type(0) and req_table_num > 0 and req_table_num <= all_tables.shape[0]
375
+ else:
376
+ req_table_num = all_tables.shape[0]
377
+ for i in range(req_table_num):
378
+ #one_table = all_tables.iloc[i]["table"]
379
+ #one_table_df = pd.read_sql("select * from `{}`".format(one_table), train_tables_dump_engine)
380
+ one_table_s = all_tables.iloc[i]
381
+ one_table_df = pd.DataFrame(one_table_s["rows"], columns = one_table_s["header"])
382
+ yield one_table_df, json_df[json_df["table_id"] == one_table_s["id"]]
383
+ ## data source end
384
+
385
+
386
+ ###### string toolkit start
387
+ def findMaxSubString(str1, str2):
388
+ """
389
+ """
390
+ maxSub = 0
391
+ maxSubString = ""
392
+
393
+ str1_len = len(str1)
394
+ str2_len = len(str2)
395
+
396
+ for i in range(str1_len):
397
+ str1_pos = i
398
+ for j in range(str2_len):
399
+ str2_pos = j
400
+ str1_pos = i
401
+ if str1[str1_pos] != str2[str2_pos]:
402
+ continue
403
+ else:
404
+ while (str1_pos < str1_len) and (str2_pos < str2_len):
405
+ if str1[str1_pos] == str2[str2_pos]:
406
+ str1_pos = str1_pos + 1
407
+ str2_pos = str2_pos + 1
408
+ else:
409
+ break
410
+
411
+ sub_len = str2_pos - j
412
+ if maxSub < sub_len:
413
+ maxSub = sub_len
414
+ maxSubString = str2[j:str2_pos]
415
+ return maxSubString
416
+
417
+
418
+ def find_min_commmon_strings(c):
419
+ ##### {"jack", "ja", "ss", "sss", "ps", ""} -> {"ja", "ss", "ps"}
420
+ common_strings = list(filter(lambda x: type(x) == type("") ,
421
+ map(lambda t2: t2[0]
422
+ if t2[0] in t2[1]
423
+ else (t2[1]
424
+ if t2[1] in t2[0]
425
+ else (t2[0], t2[1])),combinations(c, 2))))
426
+ req = set([])
427
+ while c:
428
+ ele = c.pop()
429
+ if all(map(lambda cc: cc not in ele, common_strings)):
430
+ req.add(ele)
431
+ req = req.union(set(common_strings))
432
+ return set(filter(lambda x: x, req))
433
+ ## string toolkit end
434
+
435
+
436
+
437
+ ###### datetime column match start
438
+ #### only use object dtype to extract
439
+ def time_template_extractor(rows_filtered, pattern = u"[年月\.\-\d]+"):
440
+ #re_words = re.compile(u"[年月\.\-\d]+")
441
+ re_words = re.compile(pattern)
442
+ nest_collection = pd.DataFrame(rows_filtered).applymap(lambda x: tuple(sorted(list(re.findall(re_words, x))))).values.tolist()
443
+ def flatten_collection(c):
444
+ if not c:
445
+ return c
446
+ if type(c[0]) == type(""):
447
+ return c
448
+ else:
449
+ c = list(c)
450
+ return flatten_collection(reduce(lambda a, b: a + b, map(list ,c)))
451
+ return flatten_collection(nest_collection)
452
+
453
+ ###@@ pattern_list
454
+ #pattern_list = [u"[年月\.\-\d]+", u"[年月\d]+", u"[年个月\d]+", u"[年月日\d]+"]
455
+
456
+ def justify_column_as_datetime(df, threshold = 0.8, time_template_extractor = lambda x: x):
457
+ object_columns = list(map(lambda tt2: tt2[0] ,filter(lambda t2: t2[1].name == "object" ,dict(df.dtypes).items())))
458
+ time_columns = []
459
+ for col in object_columns:
460
+ input_ = df[[col]].applymap(lambda x: "~" if type(x) != type("") else x)
461
+ output_ = time_template_extractor(input_.values.tolist())
462
+ input_ = input_.iloc[:, 0].values.tolist()
463
+ time_evidence_cnt = sum(map(lambda t2: t2[0].strip() == t2[1].strip() and t2[0] and t2[1] and t2[0] != "~" and t2[1] != "~",zip(input_, output_)))
464
+ if time_evidence_cnt > 0 and time_evidence_cnt / df.shape[0] >= threshold:
465
+ #### use evidence ratio because may have some noise in data
466
+ time_columns.append(col)
467
+ return time_columns
468
+
469
+ def justify_column_as_datetime_reduce(df, threshold = 0.8, time_template_extractor_list = list(map(lambda p: partial(time_template_extractor, pattern = p), pattern_list))):
470
+ return sorted(reduce(lambda a, b: a.union(b) ,map(lambda func: set(justify_column_as_datetime(df, threshold, func)), time_template_extractor_list)))
471
+ ## datetime column match end
472
+
473
+ ##### choose question column have a reduce function call below (choose_res_by_kws)
474
+ ##### this is a tiny first version
475
+ ###@@ time_kws = ("什么时候", "时间", "时候")
476
+ #time_kws = ("什么时候", "时间", "时候")
477
+ #####
478
+ def choose_question_column(decomp, header, df):
479
+ assert type(decomp) == type((1,)) and type(header) == type([])
480
+
481
+ time_columns = justify_column_as_datetime_reduce(df)
482
+ _, res, _ = decomp
483
+
484
+ if type(res) != type(""):
485
+ return None
486
+
487
+ #ic(res)
488
+ ##### should add time kws to it.
489
+ #time_kws = ("什么时候", "时间", "时候")
490
+ if any(map(lambda t_kw: t_kw in res, time_kws)):
491
+ if len(time_columns) == 1:
492
+ return time_columns[0]
493
+ else:
494
+ '''
495
+ return sorted(map(lambda t_col: (t_col ,len(findMaxSubString(t_col, res)) / len(t_col)), time_columns),
496
+ key = lambda t2: t2[1])[::-1][0][0]
497
+ '''
498
+ sort_list = sorted(map(lambda t_col: (t_col ,len(findMaxSubString(t_col, res)) / len(t_col)), time_columns),
499
+ key = lambda t2: t2[1])[::-1]
500
+ if sort_list:
501
+ if sort_list[0]:
502
+ return sort_list[0][0]
503
+ return None
504
+
505
+ c_res_common_dict = dict(filter(lambda t2: t2[1] ,map(lambda c: (c ,findMaxSubString(c, res)), header)))
506
+ common_ratio_c_dict = dict(map(lambda t2: (t2[0], len(t2[1]) / len(t2[0])), c_res_common_dict.items()))
507
+ common_ratio_res_dict = dict(map(lambda t2: (t2[0], len(t2[1]) / len(res)), c_res_common_dict.items()))
508
+ #ic(decomp)
509
+ #ic(common_ratio_c_dict)
510
+ #ic(common_ratio_res_dict)
511
+
512
+ if not common_ratio_c_dict or not common_ratio_res_dict:
513
+ return None
514
+
515
+ dict_0_max_key = sorted(common_ratio_c_dict.items(), key = lambda t2: t2[1])[::-1][0][0]
516
+ dict_1_max_key = sorted(common_ratio_res_dict.items(), key = lambda t2: t2[1])[::-1][0][0]
517
+ return dict_0_max_key if dict_0_max_key == dict_1_max_key else None
518
+
519
+
520
+ ##### agg-classifier start
521
+ '''
522
+ sum_count_high_kws = ('多少个', '有几个', '总共') + ('总和','一共',) + ("总数",)
523
+ mean_kws = ('平均数', '均值', '平均值', '平均')
524
+ max_kws = ('最大', '最多', '最大值', '最高')
525
+ min_kws = ('最少', '最小值', '最小', '最低')
526
+ sum_count_low_kws = ('个', '总共') + ('总和','加','总','一共','和',) + ("哪些", "查", "数量", "数") + ("几",) + ('多少', "多大") + ("总数",)
527
+ max_special_kws = ("以上", "大于")
528
+ min_special_kws = ("以下", "小于")
529
+ '''
530
+
531
+ ###@@ sum_count_high_kws = ('多少个', '有几个', '总共') + ('总和','一共',) + ("总数",)
532
+ ###@@ mean_kws = ('平均数', '均值', '平均值', '平均')
533
+ ###@@ max_kws = ('最大', '最多', '最大值', '最高')
534
+ ###@@ min_kws = ('最少', '最小值', '最小', '最低')
535
+ ###@@ sum_count_low_kws = ('个', '总共') + ('总和','加','总','一共','和',) + ("哪些", "查", "数量", "数") + ("几",) + ('多少', "多大") + ("总数",)
536
+ ###@@ max_special_kws = ("以上", "大于")
537
+ ###@@ min_special_kws = ("以下", "小于")
538
+
539
+ def simple_label_func(s, drop_header = True):
540
+ text_tokens =s.question_cut
541
+ header = list(map(lambda x: x[:x.find("(")] if (not x.startswith("(") and x.endswith(")")) else x ,s.header.split(",")))
542
+
543
+ #### not contain samples may not match in fuzzy-match, special column mapping in finance,
544
+ ### or "3" to "三"
545
+ '''
546
+ fit_collection = ('多少个', '有几个', '总共') + ('总和','一共',) + ('平均数', '均值', '平均值', '平均') + ('最大', '最多', '最大值', '最高') + ('最少', '最小值', '最小', '最低')
547
+
548
+ '''
549
+ fit_collection = sum_count_high_kws + mean_kws + max_kws + min_kws
550
+ fit_header = []
551
+ for c in header:
552
+ for kw in fit_collection:
553
+ if kw in c:
554
+ start_idx = c.find(kw)
555
+ end_idx = start_idx + len(kw)
556
+ fit_header.append(c[start_idx: end_idx])
557
+
558
+ if not drop_header:
559
+ header = []
560
+ fit_header = []
561
+
562
+ input_ = "".join(text_tokens)
563
+ for c in header + fit_header:
564
+ if c in fit_collection:
565
+ continue
566
+ input_ = input_.replace(c, "")
567
+ c0, c1 = c, c
568
+ while c0 and c0 not in fit_collection and len(c0) >= 4:
569
+ c0 = c0[1:]
570
+ if c0 in fit_collection:
571
+ break
572
+ input_ = input_.replace(c0, "")
573
+ while c1 and c1 not in fit_collection and len(c1) >= 4:
574
+ c1 = c1[:-1]
575
+ if c1 in fit_collection:
576
+ break
577
+ input_ = input_.replace(c1, "")
578
+
579
+ #ic(input_)
580
+ text_tokens = list(jieba.cut(input_))
581
+
582
+ #cat_6_collection_high_level = ('多少个', '有几个', '总共') + ('总和','一共',) + ("哪些", "查", "数量")
583
+ #cat_6_collection_high_level = ('多少个', '有几个', '总共') + ('总和','一共',)
584
+ ##### 高置信度部分 (作为是否构成使用特殊规则的判断标准)
585
+ #### case 2 部分 (高置信度有效匹配)
586
+ #cat_6_collection_high_level = ('多少个', '有几个', '总共') + ('总和','一共',)
587
+ #cat_6_collection_high_level = ('多少个', '有几个', '总共') + ('总和','一共',) + ("总数",)
588
+ cat_6_collection_high_level = sum_count_high_kws
589
+ if any(map(lambda high_level_token: high_level_token in "".join(text_tokens), cat_6_collection_high_level)):
590
+ return 6
591
+
592
+ #### 够深 够宽 规则部分, change order by header, if header have kws in , lower order
593
+ if any(map(lambda kw: kw in text_tokens, mean_kws)):
594
+ return 1
595
+ if any(map(lambda kw: kw in text_tokens, max_kws)):
596
+ return 2
597
+ if any(map(lambda kw: kw in text_tokens, min_kws)):
598
+ return 3
599
+
600
+ ##### 低置信度部分
601
+ #### case 2 部分 (低置信度尾部匹配)
602
+ cat_6_collection = sum_count_low_kws
603
+ if any(map(lambda kw: kw in text_tokens, cat_6_collection)):
604
+ return 6
605
+ if any(map(lambda token: "几" in token, text_tokens)):
606
+ return 6
607
+
608
+ #### special case 部分
609
+ if any(map(lambda kw: kw in text_tokens, max_special_kws)):
610
+ return 2
611
+ if any(map(lambda kw: kw in text_tokens, min_special_kws)):
612
+ return 3
613
+
614
+ #### 无效匹配
615
+ return 0
616
+
617
+
618
+ def simple_special_func(s, drop_header = True):
619
+ text_tokens =s.question_cut
620
+ header = list(map(lambda x: x[:x.find("(")] if (not x.startswith("(") and x.endswith(")")) else x ,s.header.split(",")))
621
+
622
+ #### not contain samples may not match in fuzzy-match, special column mapping in finance,
623
+ ### or "3" to "三"
624
+ fit_collection = sum_count_high_kws + mean_kws + max_kws + min_kws
625
+ fit_header = []
626
+ for c in header:
627
+ for kw in fit_collection:
628
+ if kw in c:
629
+ start_idx = c.find(kw)
630
+ end_idx = start_idx + len(kw)
631
+ fit_header.append(c[start_idx: end_idx])
632
+
633
+ input_ = "".join(text_tokens)
634
+ if not drop_header:
635
+ header = []
636
+ fit_header = []
637
+
638
+ for c in header + fit_header:
639
+ if c in fit_collection:
640
+ continue
641
+ input_ = input_.replace(c, "")
642
+ c0, c1 = c, c
643
+ while c0 and c0 not in fit_collection and len(c0) >= 4:
644
+ c0 = c0[1:]
645
+ if c0 in fit_collection:
646
+ break
647
+ input_ = input_.replace(c0, "")
648
+ while c1 and c1 not in fit_collection and len(c1) >= 4:
649
+ c1 = c1[:-1]
650
+ if c1 in fit_collection:
651
+ break
652
+ input_ = input_.replace(c1, "")
653
+
654
+ #ic(input_)
655
+ text_tokens = list(jieba.cut(input_))
656
+ #ic(text_tokens)
657
+
658
+ #cat_6_collection_high_level = ('多少个', '有几个', '总共') + ('总和','一共',) + ("哪些", "查", "数量")
659
+ #cat_6_collection_high_level = ('多少个', '有几个', '总共') + ('总和','一共',)
660
+ #### case 2 部分 (高置信度有效匹配)
661
+ cat_6_collection_high_level = sum_count_high_kws
662
+ if any(map(lambda high_level_token: high_level_token in "".join(text_tokens), cat_6_collection_high_level)):
663
+ return 6
664
+
665
+ #### 够深 够宽 规则部分, change order by header, if header have kws in , lower order
666
+ if any(map(lambda kw: kw in text_tokens, mean_kws)):
667
+ return 1
668
+ if any(map(lambda kw: kw in text_tokens, max_kws)):
669
+ return 2
670
+ if any(map(lambda kw: kw in text_tokens, min_kws)):
671
+ return 3
672
+
673
+ return 0
674
+
675
+
676
+ def simple_total_label_func(s):
677
+ is_special = False if simple_special_func(s) == 0 else True
678
+ if not is_special:
679
+ return 0
680
+ return simple_label_func(s)
681
+ ## agg-classifier end
682
+
683
+
684
+ ##### main block of process start
685
+ def split_by_cond(s, extract_return = True):
686
+ def recurrent_extract_cond(text):
687
+ #return np.asarray(recurrent_extract(text)[0])
688
+ #return recurrent_extract(text)[0]
689
+ return np.asarray(list(recurrent_extract(text)[0]))
690
+
691
+ question = s["question"]
692
+ res = s["rec_decomp"][1]
693
+ if question is None:
694
+ question = ""
695
+ if res is None:
696
+ res = ""
697
+
698
+ common_res = findMaxSubString(question, res)
699
+ #cond_kws = ("或", "而且", "并且", "当中")
700
+ #cond_kws = ("或", "而且" "并且" "当中")
701
+ cond_kws = conn_kws
702
+ condition_part = question.replace(common_res, "")
703
+ fit_kws = set([])
704
+ for kw in cond_kws:
705
+ if kw in condition_part and not condition_part.startswith(kw) and not condition_part.endswith(kw):
706
+ fit_kws.add(kw)
707
+ if not fit_kws:
708
+ will_return = ([condition_part.replace(" ", "") + " " + common_res], "")
709
+ if extract_return:
710
+ #return (list(map(recurrent_extract_cond, will_return[0])), will_return[1])
711
+ will_return = (np.asarray(list(map(recurrent_extract_cond, will_return[0]))) , will_return[1])
712
+ #will_return = (np.concatenate(list(filter(lambda x: x.size ,map(np.asarray ,will_return[0].tolist()))), axis = 0), will_return[1])
713
+ #will_return = (np.concatenate(list(map(np.asarray ,will_return[0].tolist())), axis = 0), will_return[1])
714
+ input_ = list(filter(lambda x: x.size ,map(np.asarray ,will_return[0].tolist())))
715
+ if input_:
716
+ will_return = (np.concatenate(input_, axis = 0), will_return[1])
717
+ else:
718
+ will_return = (np.empty((0, 3)), will_return[1])
719
+
720
+ will_return = will_return[0].reshape((-1, 3)) if will_return[0].size else np.empty((0, 3))
721
+ return will_return
722
+
723
+ fit_kw = sorted(fit_kws, key = len)[::-1][0]
724
+ condition_part_splits = condition_part.split(fit_kw)
725
+ #if fit_kw in ("或",):
726
+ if fit_kw in or_kws:
727
+ fit_kw = "or"
728
+ #elif fit_kw in ("而且", "并且", "当中",):
729
+ elif fit_kw in and_kws:
730
+ fit_kw = "and"
731
+ else:
732
+ fit_kw = ""
733
+
734
+ will_return = (list(map(lambda cond_: cond_.replace(" ", "") + " " + common_res, condition_part_splits)), fit_kw)
735
+ if extract_return:
736
+ #return (list(map(recurrent_extract_cond, will_return[0])), will_return[1])
737
+ will_return = (np.asarray(list(map(recurrent_extract_cond, will_return[0]))), will_return[1])
738
+ #ic(will_return[0])
739
+ #will_return = (np.concatenate(list(map(np.asarray ,will_return[0].tolist())), axis = 0), will_return[1])
740
+ input_ = list(filter(lambda x: x.size ,map(np.asarray ,will_return[0].tolist())))
741
+ if input_:
742
+ will_return = (np.concatenate(input_, axis = 0), will_return[1])
743
+ else:
744
+ will_return = (np.empty((0, 3)), will_return[1])
745
+ #ic(will_return[0])
746
+ will_return = will_return[0].reshape((-1, 3)) if will_return[0].size else np.empty((0, 3))
747
+
748
+ return will_return
749
+
750
+
751
+
752
+ def filter_total_conds(s, df, condition_fit_num = 0):
753
+ assert condition_fit_num >= 0 and type(condition_fit_num) == type(0)
754
+ df = df.copy()
755
+
756
+ #### some col not as float with only "None" as cell, also transform them into float
757
+ df = df.applymap(lambda x: np.nan if x in ["None", None, "/"] else x)
758
+ def justify_column_as_float(s):
759
+ if "float" in str(s.dtype):
760
+ return True
761
+ if all(s.map(type).map(lambda tx: "float" in str(tx))):
762
+ return True
763
+ return False
764
+
765
+ float_cols = list(map(lambda tt2: tt2[0],filter(lambda t2: t2[1] ,df.apply(justify_column_as_float, axis = 0).to_dict().items())))
766
+ for f_col in float_cols:
767
+ df[f_col] = df[f_col].astype(np.float64)
768
+ ###
769
+
770
+ header = df.columns.tolist()
771
+ units_cols = filter(lambda c: "(" in c and c.endswith(")"), df.columns.tolist())
772
+ if not float_cols:
773
+ float_discribe_df = pd.DataFrame()
774
+ else:
775
+ float_discribe_df = df[float_cols].describe()
776
+
777
+ def call_eval(val):
778
+ try:
779
+ return literal_eval(val)
780
+ except:
781
+ return val
782
+
783
+ #### find condition column same as question_column
784
+ def find_cond_col(res, header):
785
+ #ic(res, header)
786
+ c_res_common_dict = dict(filter(lambda t2: t2[1] ,map(lambda c: (c ,findMaxSubString(c, res)), header)))
787
+ #ic(c_res_common_dict)
788
+ common_ratio_c_dict = dict(map(lambda t2: (t2[0], len(t2[1]) / len(t2[0])), c_res_common_dict.items()))
789
+ common_ratio_res_dict = dict(map(lambda t2: (t2[0], len(t2[1]) / len(res)), c_res_common_dict.items()))
790
+
791
+ if not common_ratio_c_dict or not common_ratio_res_dict:
792
+ return None
793
+
794
+ dict_0_max_key = sorted(common_ratio_c_dict.items(), key = lambda t2: t2[1])[::-1][0][0]
795
+ dict_1_max_key = sorted(common_ratio_res_dict.items(), key = lambda t2: t2[1])[::-1][0][0]
796
+ return dict_0_max_key if dict_0_max_key == dict_1_max_key else None
797
+ ###
798
+
799
+ #### type comptatible in column type and value type, and fit_num match
800
+ def filter_cond_col(cond_t3):
801
+ assert type(cond_t3) == type((1,)) and len(cond_t3) == 3
802
+ col, _, value = cond_t3
803
+
804
+ if type(value) == type(""):
805
+ value = call_eval(value)
806
+
807
+ if col not in df.columns.tolist():
808
+ return False
809
+
810
+ #### type key value comp
811
+ if col in float_cols and type(value) not in (type(0), type(0.0)):
812
+ return False
813
+
814
+ if col not in float_cols and type(value) in (type(0), type(0.0)):
815
+ return False
816
+
817
+ #### string value not in corr column
818
+ if col not in float_cols and type(value) not in (type(0), type(0.0)):
819
+ if type(value) == type(""):
820
+ if value not in df[col].tolist():
821
+ return False
822
+
823
+ if type(value) in (type(0), type(0.0)):
824
+ if col in float_discribe_df.columns.tolist():
825
+ if condition_fit_num > 0:
826
+ if value >= float_discribe_df[col].loc["min"] and value <= float_discribe_df[col].loc["max"]:
827
+ return True
828
+ else:
829
+ return False
830
+ else:
831
+ assert condition_fit_num == 0
832
+ return True
833
+
834
+ if condition_fit_num > 0:
835
+ if value in df[col].tolist():
836
+ return True
837
+ else:
838
+ return False
839
+ else:
840
+ assert condition_fit_num == 0
841
+ return True
842
+
843
+ return True
844
+ ###
845
+
846
+ #### condtions with same column may have conflict, choose the nearest one by stats in float or
847
+ ### common_string as find_cond_col do.
848
+ def same_column_cond_filter(cond_list, sort_stats = "mean"):
849
+ #ic(cond_list)
850
+ if len(cond_list) == len(set(map(lambda t3: t3[0] ,cond_list))):
851
+ return cond_list
852
+
853
+ req = defaultdict(list)
854
+ for t3 in cond_list:
855
+ req[t3[0]].append(t3[1:])
856
+
857
+ def t2_list_sort(col_name ,t2_list):
858
+ if not t2_list:
859
+ return None
860
+ t2 = None
861
+ if col_name in float_cols:
862
+ t2 = sorted(t2_list, key = lambda t2: np.abs(t2[1] - float_discribe_df[col_name].loc[sort_stats]))[0]
863
+ else:
864
+ if all(map(lambda t2: type(t2[1]) == type("") ,t2_list)):
865
+ col_val_cnt_df = df[col_name].value_counts().reset_index()
866
+ col_val_cnt_df.columns = ["val", "cnt"]
867
+ #col_val_cnt_df["val"].map(lambda x: sorted(filter(lambda tt2: tt2[-1] ,map(lambda t2: (t2 ,len(findMaxSubString(x, t2[1]))), t2_list)),
868
+ # key = lambda ttt2: -1 * ttt2[-1])[0])
869
+
870
+ t2_list_map_to_column_val = list(filter(lambda x: x[1] ,map(lambda t2: (t2[0] ,find_cond_col(t2[1], list(set(col_val_cnt_df["val"].values.tolist())))), t2_list)))
871
+ if t2_list_map_to_column_val:
872
+ #### return max length fit val in column
873
+ t2 = sorted(t2_list_map_to_column_val, key = lambda t2: -1 * len(t2[1]))[0]
874
+ if t2 is None and t2_list:
875
+ t2 = t2_list[0]
876
+ return t2
877
+
878
+ cond_list_filtered = list(map(lambda ttt2: (ttt2[0], ttt2[1][0], ttt2[1][1]) ,
879
+ filter(lambda tt2: tt2[1] ,map(lambda t2: (t2[0] ,t2_list_sort(t2[0], t2[1])), req.items()))))
880
+
881
+ return cond_list_filtered
882
+ ###
883
+
884
+ total_conds_map_to_column = list(map(lambda t3: (find_cond_col(t3[0], header), t3[1], t3[2]), s["total_conds"]))
885
+ total_conds_map_to_column_filtered = list(filter(filter_cond_col, total_conds_map_to_column))
886
+ total_conds_map_to_column_filtered = sorted(set(map(lambda t3: (t3[0], t3[1], call_eval(t3[2]) if type(t3[2]) == type("") else t3[2]), total_conds_map_to_column_filtered)))
887
+ #ic(total_conds_map_to_column_filtered)
888
+
889
+ cp_cond_list = list(filter(lambda t3: t3[1] in (">", "<"), total_conds_map_to_column_filtered))
890
+ eq_cond_list = list(filter(lambda t3: t3[1] in ("==", "!="), total_conds_map_to_column_filtered))
891
+
892
+ cp_cond_list_filtered = same_column_cond_filter(cp_cond_list)
893
+
894
+ #total_conds_map_to_column_filtered = same_column_cond_filter(total_conds_map_to_column_filtered)
895
+ return cp_cond_list_filtered + eq_cond_list
896
+ #return total_conds_map_to_column_filtered
897
+
898
+ ###@@ only_kws_columns = {"城市": "=="}
899
+
900
+ #### this function only use to cond can not extract by JointBert,
901
+ ### may because not contain column string in question such as "城市" or difficult to extract kw
902
+ ### define kw column as all cells in series are string type.
903
+ ### this function support config relation to column and if future
904
+ ### want to auto extract relation, this may can be done by head string or tail string by edit pattern "\w?{}\w?"
905
+ ### "是" or "不是" can be extract in this manner.
906
+ def augment_kw_in_question(question_df, df, only_kws_in_string = []):
907
+ #### keep only_kws_in_string empty to maintain all condition
908
+ question_df = question_df.copy()
909
+ #df = df.copy()
910
+
911
+ def call_eval(val):
912
+ try:
913
+ return literal_eval(val)
914
+ except:
915
+ return val
916
+
917
+ df = df.copy()
918
+
919
+ df = df.applymap(call_eval)
920
+
921
+ #### some col not as float with only "None" as cell, also transform them into float
922
+ df = df.applymap(lambda x: np.nan if x in ["None", None, "/"] else x)
923
+ def justify_column_as_float(s):
924
+ if "float" in str(s.dtype):
925
+ return True
926
+ if all(s.map(type).map(lambda tx: "float" in str(tx))):
927
+ return True
928
+ return False
929
+
930
+ float_cols = list(map(lambda tt2: tt2[0],filter(lambda t2: t2[1] ,df.apply(justify_column_as_float, axis = 0).to_dict().items())))
931
+ #obj_cols = set(df.columns.tolist()).difference(set(float_cols))
932
+
933
+ def justify_column_as_kw(s):
934
+ if all(s.map(type).map(lambda tx: "str" in str(tx))):
935
+ return True
936
+ return False
937
+
938
+ obj_cols = list(map(lambda tt2: tt2[0],filter(lambda t2: t2[1] ,df.apply(justify_column_as_kw, axis = 0).to_dict().items())))
939
+ obj_cols = list(set(obj_cols).difference(set(float_cols)))
940
+ if only_kws_columns:
941
+ obj_cols = list(set(obj_cols).intersection(set(only_kws_columns.keys())))
942
+
943
+ #replace_format = "{}是{}"
944
+ #kw_augmented_df = pd.DataFrame(df[obj_cols].apply(lambda s: list(map(lambda val :(val,replace_format.format(s.name, val)), s.tolist())), axis = 0).values.tolist())
945
+ #kw_augmented_df.columns = obj_cols
946
+ kw_augmented_df = df[obj_cols].copy()
947
+ #ic(kw_augmented_df)
948
+
949
+ def extract_question_kws(question):
950
+ if not kw_augmented_df.size:
951
+ return []
952
+ req = defaultdict(set)
953
+ for ridx, r in kw_augmented_df.iterrows():
954
+ for k, v in dict(r).items():
955
+ if v in question:
956
+ pattern = "\w?{}\w?".format(v)
957
+ all_match = re.findall(pattern, question)
958
+ #req = req.union(set(all_match))
959
+ #req[v] = req[v].union(set(all_match))
960
+ key = "{}~{}".format(k, v)
961
+ req[key] = req[key].union(set(all_match))
962
+ #ic(k, v)
963
+ #question = question.replace(v[0], v[1])
964
+ #return question.replace(replace_format.format("","") * 2, replace_format.format("",""))
965
+ #req = list(req)
966
+ if only_kws_in_string:
967
+ req = list(map(lambda tt2: tt2[0] ,filter(lambda t2: sum(map(lambda kw: sum(map(lambda t: kw in t ,t2[1])), only_kws_in_string)), req.items())))
968
+ else:
969
+ req = list(set(req.keys()))
970
+
971
+ def req_to_t3(req_string, relation = "=="):
972
+ assert "~" in req_string
973
+ left, right = req_string.split("~")
974
+ if left in only_kws_columns:
975
+ relation = only_kws_columns[left]
976
+ return (left, relation, right)
977
+
978
+ if not req:
979
+ return []
980
+
981
+ return list(map(req_to_t3, req))
982
+
983
+ #return req
984
+
985
+ question_df["question_kw_conds"] = question_df["question"].map(extract_question_kws)
986
+ return question_df
987
+
988
+
989
+ def choose_question_column_by_rm_conds(s, df):
990
+ question = s.question
991
+ total_conds_filtered = s.total_conds_filtered
992
+ #cond_kws = ("或", "而且", "并且", "当中")
993
+ cond_kws = conn_kws
994
+ stopwords = ("是", )
995
+ #ic(total_conds_filtered)
996
+ def construct_res(question):
997
+ for k, _, v in total_conds_filtered:
998
+ if "(" in k:
999
+ k = k[:k.find("(")]
1000
+ #ic(k)
1001
+ question = question.replace(str(k), "")
1002
+ question = question.replace(str(v), "")
1003
+ for w in cond_kws + stopwords:
1004
+ question = question.replace(w, "")
1005
+ return question
1006
+
1007
+ res = construct_res(question)
1008
+ decomp = (None, res, None)
1009
+ return choose_question_column(decomp, df.columns.tolist(), df)
1010
+
1011
+
1012
+ def split_qst_by_kw(question, kw = "的"):
1013
+ return question.split(kw)
1014
+
1015
+ #qst_kws = ("多少", "什么", "多大", "哪些", "怎么", "情况", "那些", "哪个")
1016
+ ###@@ qst_kws = ("多少", "什么", "多大", "哪些", "怎么", "情况", "那些", "哪个")
1017
+ def choose_res_by_kws(question):
1018
+ #kws = ["的","多少", '是']
1019
+ question = question.replace(" ", "")
1020
+ #kws = ["的","或者","或", "且","并且","同时"]
1021
+ kws = ("的",) + conn_kws
1022
+ kws = list(kws)
1023
+ def qst_kw_filter(text):
1024
+ #qst_kws = ("多少", "什么", "多大", "哪些", "怎么", "情况", "那些", "哪个")
1025
+ if any(map(lambda kw: kw in text, qst_kws)):
1026
+ return True
1027
+ return False
1028
+
1029
+ kws_cp = deepcopy(kws)
1030
+ qst_c = set(question.split(","))
1031
+ while kws:
1032
+ kw = kws.pop()
1033
+ qst_c = qst_c.union(set(filter(qst_kw_filter ,reduce(lambda a, b: a + b,map(lambda q: split_qst_by_kw(q, kw), qst_c))))
1034
+ )
1035
+ #print("-" * 10)
1036
+ #print(sorted(filter(lambda x: x and (x not in kws_cp) ,qst_c), key = len))
1037
+ #print(sorted(filter(lambda x: x and (x not in kws_cp) and qst_kw_filter(x) ,qst_c), key = len))
1038
+ #### final choose if or not
1039
+ return sorted(filter(lambda x: x and (x not in kws_cp) and qst_kw_filter(x) ,qst_c), key = len)
1040
+ #return sorted(filter(lambda x: x and (x not in kws_cp) and True ,qst_c), key = len)
1041
+
1042
+
1043
+ def cat6_to_45_by_column_type(s, df):
1044
+ agg_pred = s.agg_pred
1045
+ if agg_pred != 6:
1046
+ return agg_pred
1047
+ question_column = s.question_column
1048
+
1049
+ def call_eval(val):
1050
+ try:
1051
+ return literal_eval(val)
1052
+ except:
1053
+ return val
1054
+
1055
+ df = df.copy()
1056
+
1057
+ df = df.applymap(call_eval)
1058
+
1059
+ #### some col not as float with only "None" as cell, also transform them into float
1060
+ df = df.applymap(lambda x: np.nan if x in ["None", None, "/"] else x)
1061
+ def justify_column_as_float(s):
1062
+ if "float" in str(s.dtype):
1063
+ return True
1064
+ if all(s.map(type).map(lambda tx: "float" in str(tx))):
1065
+ return True
1066
+ return False
1067
+
1068
+ float_cols = list(map(lambda tt2: tt2[0],filter(lambda t2: t2[1] ,df.apply(justify_column_as_float, axis = 0).to_dict().items())))
1069
+ #obj_cols = set(df.columns.tolist()).difference(set(float_cols))
1070
+
1071
+ def justify_column_as_kw(s):
1072
+ if all(s.map(type).map(lambda tx: "str" in str(tx))):
1073
+ return True
1074
+ return False
1075
+
1076
+ #obj_cols = list(map(lambda tt2: tt2[0],filter(lambda t2: t2[1] ,df.apply(justify_column_as_kw, axis = 0).to_dict().items())))
1077
+ obj_cols = df.columns.tolist()
1078
+ obj_cols = list(set(obj_cols).difference(set(float_cols)))
1079
+
1080
+ #ic(obj_cols, float_cols, df.columns.tolist())
1081
+ assert len(obj_cols) + len(float_cols) == df.shape[1]
1082
+
1083
+ if question_column in obj_cols:
1084
+ return 4
1085
+ elif question_column in float_cols:
1086
+ return 5
1087
+ else:
1088
+ return 0
1089
+
1090
+
1091
+ def full_before_cat_decomp(df, question_df, only_req_columns = False):
1092
+ df, question_df = df.copy(), question_df.copy()
1093
+ first_train_question_extract_df = pd.DataFrame(question_df["question"].map(lambda question: (question, recurrent_extract(question))).tolist())
1094
+ first_train_question_extract_df.columns = ["question", "decomp"]
1095
+
1096
+ first_train_question_extract_df = augment_kw_in_question(first_train_question_extract_df, df)
1097
+
1098
+ first_train_question_extract_df["rec_decomp"] = first_train_question_extract_df["decomp"].map(lambda decomp: decomp if decomp[0] else rec_more_time(decomp))
1099
+ #return first_train_question_extract_df.copy()
1100
+ first_train_question_extract_df["question_cut"] = first_train_question_extract_df["rec_decomp"].map(lambda t3: jieba.cut(t3[1]) if t3[1] is not None else []).map(list)
1101
+ first_train_question_extract_df["header"] = ",".join(df.columns.tolist())
1102
+ first_train_question_extract_df["question_column_res"] = first_train_question_extract_df["rec_decomp"].map(lambda decomp: choose_question_column(decomp, df.columns.tolist(), df))
1103
+
1104
+ #### agg
1105
+ first_train_question_extract_df["agg_res_pred"] = first_train_question_extract_df.apply(simple_total_label_func, axis = 1)
1106
+ first_train_question_extract_df["question_cut"] = first_train_question_extract_df["question"].map(jieba.cut).map(list)
1107
+ first_train_question_extract_df["agg_qst_pred"] = first_train_question_extract_df.apply(simple_total_label_func, axis = 1)
1108
+ ### if agg_res_pred and agg_qst_pred have conflict use max, to prevent from empty agg with errorous question column
1109
+ ### but this "max" can also be replaced by measure the performance of decomp part, and choose the best one
1110
+ ### or we can use agg_qst_pred with high balanced_score as 0.86+ in imbalanced dataset.
1111
+ ### which operation to use need some discussion.
1112
+ ### (balanced_accuracy_score(lookup_df["sql"], lookup_df["agg_pred"]),
1113
+ ### balanced_accuracy_score(lookup_df["sql"], lookup_df["agg_res_pred"]),
1114
+ ### balanced_accuracy_score(lookup_df["sql"], lookup_df["agg_qst_pred"]))
1115
+ ### (0.9444444444444445, 0.861111111111111, 0.9444444444444445) first_train_df conclucion
1116
+ ### (1.0, 0.8333333333333333, 1.0) cat6_conclucion
1117
+ ### this show that res worse in cat6 situation, but the agg-classifier construct is sufficent to have a
1118
+ ### good conclusion in full-question. (because cat6 is the most accurate part in Tupledire tree sense.)
1119
+ ### so use max as the best one
1120
+ first_train_question_extract_df["agg_pred"] = first_train_question_extract_df.apply(lambda s: max(s.agg_res_pred, s.agg_qst_pred), axis = 1)
1121
+
1122
+ #### conn and conds
1123
+ first_train_question_extract_df["conds"] = first_train_question_extract_df["rec_decomp"].map(lambda x: x[0])
1124
+ first_train_question_extract_df["split_conds"] = first_train_question_extract_df.apply(split_by_cond, axis = 1).values.tolist()
1125
+ first_train_question_extract_df["conn_pred"] = first_train_question_extract_df.apply(lambda s: split_by_cond(s, extract_return=False), axis = 1).map(lambda x: x[-1]).values.tolist()
1126
+ #first_train_question_extract_df["total_conds"] = first_train_question_extract_df.apply(lambda s: list(set(map(tuple,s["conds"] + s["split_conds"].tolist()))), axis = 1).values.tolist()
1127
+ first_train_question_extract_df["total_conds"] = first_train_question_extract_df.apply(lambda s: list(set(map(tuple,s["question_kw_conds"] + s["conds"] + s["split_conds"].tolist()))), axis = 1).values.tolist()
1128
+ first_train_question_extract_df["total_conds_filtered"] = first_train_question_extract_df.apply(lambda s: filter_total_conds(s, df), axis = 1).values.tolist()
1129
+
1130
+ #### question_column_res more accurate, if not fit then use full-question question_column_qst to extract
1131
+ ### can not fit multi question or fuzzy describe, or question need kw replacement.
1132
+
1133
+ #first_train_question_extract_df["question_column_qst"] = first_train_question_extract_df.apply(lambda s: choose_question_column_by_rm_conds(s, df), axis = 1)
1134
+ first_train_question_extract_df["question_column_qst"] = first_train_question_extract_df["question"].map(choose_res_by_kws).map(lambda res_list: list(filter(lambda x: x ,map(lambda res: choose_question_column((None, res, None), df.columns.tolist(), df), res_list)))).map(lambda x: x[0] if x else None)
1135
+ first_train_question_extract_df["question_column"] = first_train_question_extract_df.apply(lambda s: s.question_column_res if s.question_column_res is not None else s.question_column_qst, axis = 1)
1136
+
1137
+ #### predict cat6 to 4 5 based on question_column and column dtype,
1138
+ #### this may performance bad if question_column has error,
1139
+ #### and almost 100% accurate if question_column truly provide and user is not an idoit (speak ....)
1140
+ agg_sql_dict = {0:"", 1:"AVG", 2:"MAX", 3:"MIN", 4:"COUNT", 5:"SUM"}
1141
+ first_train_question_extract_df["agg_pred"] = first_train_question_extract_df.apply(lambda s: cat6_to_45_by_column_type(s, df), axis = 1).map(lambda x: agg_sql_dict[x])
1142
+ if only_req_columns:
1143
+ return first_train_question_extract_df[["question",
1144
+ "total_conds_filtered",
1145
+ "conn_pred",
1146
+ "question_column",
1147
+ "agg_pred"
1148
+ ]].copy()
1149
+
1150
+ return first_train_question_extract_df.copy()
1151
+
1152
+
1153
+ if __name__ == "__main__":
1154
+ ###### valid block
1155
+ req = list(data_loader(req_table_num=None))
1156
+
1157
+
1158
+ train_df, _ = req[2]
1159
+ train_df
1160
+ question = "哪些股票的收盘价大于20?"
1161
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1162
+ ic(question)
1163
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1164
+
1165
+
1166
+ #### not support select 股票 from table where 市值 = (select max(市��) from table)
1167
+ #### this is a nest sql.
1168
+ question = "哪个股票代码市值最高?"
1169
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1170
+ ic(question)
1171
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1172
+
1173
+ question = "市值的最大值是多少?"
1174
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1175
+ ic(question)
1176
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1177
+
1178
+
1179
+ question = "EPS大于0的股票有哪些?"
1180
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1181
+ ic(question)
1182
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1183
+
1184
+
1185
+ question = "EPS大于0且周涨跌大于5的平均市值是多少?"
1186
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1187
+ ic(question)
1188
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1189
+
1190
+
1191
+ train_df, _ = req[5]
1192
+ train_df
1193
+ question = "产能小于20、销量大于40而且市场占有率超过1的公司有哪些?"
1194
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1195
+ ic(question)
1196
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1197
+
1198
+
1199
+ #### 特殊符号 "、"
1200
+ question = "产能小于20而且销量大于40而且市场占有率超过1的公司有哪些?"
1201
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1202
+ ic(question)
1203
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1204
+
1205
+
1206
+ train_df, _ = req[6]
1207
+ train_df
1208
+ #### 加入列别名 只需要 复刻列即可
1209
+ question = "投资评级为维持的名称有哪些?"
1210
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1211
+ ic(question)
1212
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1213
+
1214
+
1215
+ train_df["公司"] = train_df["名称"]
1216
+ question = "投资评级为维持的公司有哪些?"
1217
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1218
+ ic(question)
1219
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1220
+
1221
+
1222
+ question = "投资评级为维持而且变动为增持的公司有哪些?"
1223
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1224
+ ic(question)
1225
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1226
+
1227
+
1228
+ question = "投资评级为维持或者变动为增持的公司有哪些?"
1229
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1230
+ ic(question)
1231
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1232
+
1233
+
1234
+ question = "投资评级为维持或者变动为增持的平均收盘价是多少?"
1235
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1236
+ ic(question)
1237
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1238
+
1239
+
1240
+ train_df, _ = req[7]
1241
+ train_df
1242
+ question = "宁波的一手房每周交易数据上周成交量是多少?"
1243
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1244
+ ic(question)
1245
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1246
+
1247
+
1248
+ question = "一手房每周交易数据为宁波上周成交量是多少?"
1249
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1250
+ ic(question)
1251
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1252
+
1253
+ #### this also can deal with set column as use kw to extract
1254
+ ### see function augment_kw_in_question
1255
+ train_df["城市"] = train_df["一手房每周交易数据"]
1256
+ question = "一手房每周交易数据为宁波上周成交量是多少?"
1257
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1258
+ ic(question)
1259
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1260
+
1261
+ question = "王翔知道宁波一手房的当月累计成交量是多少吗?"
1262
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1263
+ ic(question)
1264
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1265
+
1266
+
1267
+ question = "王翔知道上周成交量大于50的最大同比当月是多少吗?"
1268
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1269
+ ic(question)
1270
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1271
+
1272
+
1273
+ train_df, _ = req[9]
1274
+ #### the last column should be "周跌幅", can't tackle duplicates columns
1275
+ train_df
1276
+ cols = train_df.columns.tolist()
1277
+ cols[-1] = "周跌幅(%)"
1278
+ train_df.columns = cols
1279
+ question = "周涨幅大于7的涨股有哪些?"
1280
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1281
+ ic(question)
1282
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1283
+
1284
+
1285
+ #### not recognize as 6 agg-classifier
1286
+ question = "周涨幅大于7的涨股总数是多少?"
1287
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1288
+ ic(question)
1289
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
1290
+
1291
+
1292
+ question = "周涨幅大于7的涨股总共有多少个?"
1293
+ qs_df = pd.DataFrame([[question]], columns = ["question"])
1294
+ ic(question)
1295
+ ic(full_before_cat_decomp(train_df, qs_df, only_req_columns=True))
JointBERT-master/.gitignore ADDED
@@ -0,0 +1,114 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Byte-compiled / optimized / DLL files
2
+ __pycache__/
3
+ *.py[cod]
4
+ *$py.class
5
+
6
+ # C extensions
7
+ *.so
8
+
9
+ # Distribution / packaging
10
+ .Python
11
+ build/
12
+ develop-eggs/
13
+ dist/
14
+ downloads/
15
+ eggs/
16
+ .eggs/
17
+ lib/
18
+ lib64/
19
+ parts/
20
+ sdist/
21
+ var/
22
+ wheels/
23
+ *.egg-info/
24
+ .installed.cfg
25
+ *.egg
26
+ MANIFEST
27
+
28
+ # PyInstaller
29
+ # Usually these files are written by a python script from a template
30
+ # before PyInstaller builds the exe, so as to inject date/other infos into it.
31
+ *.manifest
32
+ *.spec
33
+
34
+ # Installer logs
35
+ pip-log.txt
36
+ pip-delete-this-directory.txt
37
+
38
+ # Unit test / coverage reports
39
+ htmlcov/
40
+ .tox/
41
+ .coverage
42
+ .coverage.*
43
+ .cache
44
+ nosetests.xml
45
+ coverage.xml
46
+ *.cover
47
+ .hypothesis/
48
+ .pytest_cache/
49
+
50
+ # Translations
51
+ *.mo
52
+ *.pot
53
+
54
+ # Django stuff:
55
+ *.log
56
+ local_settings.py
57
+ db.sqlite3
58
+
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+ # Flask stuff:
60
+ instance/
61
+ .webassets-cache
62
+
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+ # Scrapy stuff:
64
+ .scrapy
65
+
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+ # Sphinx documentation
67
+ docs/_build/
68
+
69
+ # PyBuilder
70
+ target/
71
+
72
+ # Jupyter Notebook
73
+ .ipynb_checkpoints
74
+
75
+ # pyenv
76
+ .python-version
77
+
78
+ # celery beat schedule file
79
+ celerybeat-schedule
80
+
81
+ # SageMath parsed files
82
+ *.sage.py
83
+
84
+ # Environments
85
+ .env
86
+ .venv
87
+ env/
88
+ venv/
89
+ ENV/
90
+ env.bak/
91
+ venv.bak/
92
+
93
+ # Spyder project settings
94
+ .spyderproject
95
+ .spyproject
96
+
97
+ # Rope project settings
98
+ .ropeproject
99
+
100
+ # mkdocs documentation
101
+ /site
102
+
103
+ # mypy
104
+ .mypy_cache/
105
+
106
+ ###################################
107
+ .vscode/
108
+ .idea/
109
+ snips_model/
110
+ atis_model/
111
+
112
+ .DS_Store
113
+ cached*
114
+ sample_pred_out.txt
JointBERT-master/LICENSE ADDED
@@ -0,0 +1,201 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Apache License
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+ Version 2.0, January 2004
3
+ http://www.apache.org/licenses/
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+
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+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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JointBERT-master/README.md ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # JointBERT
2
+
3
+ (Unofficial) Pytorch implementation of `JointBERT`: [BERT for Joint Intent Classification and Slot Filling](https://arxiv.org/abs/1902.10909)
4
+
5
+ ## Model Architecture
6
+
7
+ <p float="left" align="center">
8
+ <img width="600" src="https://user-images.githubusercontent.com/28896432/68875755-b2f92900-0746-11ea-8819-401d60e4185f.png" />
9
+ </p>
10
+
11
+ - Predict `intent` and `slot` at the same time from **one BERT model** (=Joint model)
12
+ - total_loss = intent_loss + coef \* slot_loss (Change coef with `--slot_loss_coef` option)
13
+ - **If you want to use CRF layer, give `--use_crf` option**
14
+
15
+ ## Dependencies
16
+
17
+ - python>=3.6
18
+ - torch==1.6.0
19
+ - transformers==3.0.2
20
+ - seqeval==0.0.12
21
+ - pytorch-crf==0.7.2
22
+
23
+ ## Dataset
24
+
25
+ | | Train | Dev | Test | Intent Labels | Slot Labels |
26
+ | ----- | ------ | --- | ---- | ------------- | ----------- |
27
+ | ATIS | 4,478 | 500 | 893 | 21 | 120 |
28
+ | Snips | 13,084 | 700 | 700 | 7 | 72 |
29
+
30
+ - The number of labels are based on the _train_ dataset.
31
+ - Add `UNK` for labels (For intent and slot labels which are only shown in _dev_ and _test_ dataset)
32
+ - Add `PAD` for slot label
33
+
34
+ ## Training & Evaluation
35
+
36
+ ```bash
37
+ $ python3 main.py --task {task_name} \
38
+ --model_type {model_type} \
39
+ --model_dir {model_dir_name} \
40
+ --do_train --do_eval \
41
+ --use_crf
42
+
43
+ # For ATIS
44
+ $ python3 main.py --task atis \
45
+ --model_type bert \
46
+ --model_dir atis_model \
47
+ --do_train --do_eval
48
+ # For Snips
49
+ $ python3 main.py --task snips \
50
+ --model_type bert \
51
+ --model_dir snips_model \
52
+ --do_train --do_eval
53
+ ```
54
+
55
+ ## Prediction
56
+
57
+ ```bash
58
+ $ python3 predict.py --input_file {INPUT_FILE_PATH} --output_file {OUTPUT_FILE_PATH} --model_dir {SAVED_CKPT_PATH}
59
+ ```
60
+
61
+ ## Results
62
+
63
+ - Run 5 ~ 10 epochs (Record the best result)
64
+ - Only test with `uncased` model
65
+ - ALBERT xxlarge sometimes can't converge well for slot prediction.
66
+
67
+ | | | Intent acc (%) | Slot F1 (%) | Sentence acc (%) |
68
+ | --------- | ---------------- | -------------- | ----------- | ---------------- |
69
+ | **Snips** | BERT | **99.14** | 96.90 | 93.00 |
70
+ | | BERT + CRF | 98.57 | **97.24** | **93.57** |
71
+ | | DistilBERT | 98.00 | 96.10 | 91.00 |
72
+ | | DistilBERT + CRF | 98.57 | 96.46 | 91.85 |
73
+ | | ALBERT | 98.43 | 97.16 | 93.29 |
74
+ | | ALBERT + CRF | 99.00 | 96.55 | 92.57 |
75
+ | **ATIS** | BERT | 97.87 | 95.59 | 88.24 |
76
+ | | BERT + CRF | **97.98** | 95.93 | 88.58 |
77
+ | | DistilBERT | 97.76 | 95.50 | 87.68 |
78
+ | | DistilBERT + CRF | 97.65 | 95.89 | 88.24 |
79
+ | | ALBERT | 97.64 | 95.78 | 88.13 |
80
+ | | ALBERT + CRF | 97.42 | **96.32** | **88.69** |
81
+
82
+ ## Updates
83
+
84
+ - 2019/12/03: Add DistilBert and RoBERTa result
85
+ - 2019/12/14: Add Albert (large v1) result
86
+ - 2019/12/22: Available to predict sentences
87
+ - 2019/12/26: Add Albert (xxlarge v1) result
88
+ - 2019/12/29: Add CRF option
89
+ - 2019/12/30: Available to check `sentence-level semantic frame accuracy`
90
+ - 2020/01/23: Only show the result related with uncased model
91
+ - 2020/04/03: Update with new prediction code
92
+
93
+ ## References
94
+
95
+ - [Huggingface Transformers](https://github.com/huggingface/transformers)
96
+ - [pytorch-crf](https://github.com/kmkurn/pytorch-crf)
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1
+ i want to fly from boston at 838 am and arrive in denver at 1110 in the morning
2
+ show me all round trip flights between houston and las vegas
3
+ i would like some information on a flight from denver to san francisco on united airlines
4
+ what are the coach flights between dallas and baltimore leaving august tenth and returning august twelve
5
+ i'm flying from boston to the bay area
6
+ okay can you tell me the flight cost between denver and atlanta
7
+ from montreal to las vegas
8
+ what is the earliest breakfast flight from philadelphia to fort worth
9
+ flights from pittsburgh to baltimore between 10 am and 2 pm
10
+ what is the latest flight departing from boston to san francisco
11
+ flights from ontario to florida
12
+ i would like to know the first class fare on a flight from baltimore to denver
13
+ okay that sounds great let's go from atlanta on april twenty one in the morning to dallas least expensive fare one way
14
+ show me the prices of all flights from atlanta to washington dc
15
+ flights from cincinnati to o'hare departing after 718 am american
16
+ i'm interested in a flight from pittsburgh to atlanta
17
+ i am interested in booking an early morning flight from dallas into houston on february twenty second and returning late in the evening of february twenty second
18
+ i'm looking for a flight from oakland to denver with a stopover in dallas fort worth
19
+ what's restriction ap68
20
+ what types of ground transportation are available in philadelphia
21
+ what does the abbreviation co mean
22
+ a first class flight on american to san francisco on the coming tuesday
23
+ please list the flights from baltimore to san francisco on fridays
24
+ what flights return from denver to philadelphia on a saturday
25
+ on united airlines flying from denver to san francisco before 10 am what type of aircraft is used
26
+ i need a flight from atlanta to baltimore nonstop arriving at 7 pm please
27
+ what are the cheapest round trip flights from denver to atlanta
28
+ does continental fly from denver to san francisco
29
+ i would like a nonstop flight from st. petersburg to charlotte leaving in the afternoon
30
+ on continental airlines any class service from san francisco to pittsburgh
31
+ find me the cheapest flight from boston to washington
32
+ well i'll try last time tell me the kind of aircraft united airlines flies from denver to san francisco before 10 o'clock in the morning
33
+ show me the northwest flights from detroit to st. petersburg
34
+ morning flights from pittsburgh to atlanta on wednesday
35
+ show me flights first class from san francisco to pittsburgh leaving on tuesday after 8 o'clock in the morning and before 12 noon
36
+ what's the most expensive way i can fly to washington
37
+ show me the cheapest one way fare from baltimore to dallas
38
+ flights from boston flights from philadelphia to boston on monday
39
+ list nonstop flights from houston to dallas which arrive before midnight
40
+ i need a flight to seattle leaving from baltimore making a stop in minneapolis
41
+ philadelphia to san francisco please
42
+ airline that stands for dl
43
+ i'd like a cheap flight from dallas to baltimore on january first
44
+ what flights are available friday from san francisco to boston
45
+ show me saturday and sunday's flights from milwaukee to phoenix on american airlines
46
+ what flights from st. paul to kansas city on friday with lunch served
47
+ what flights from toronto to philadelphia
48
+ what flights leave from atlanta to boston on june twenty ninth in the afternoon
49
+ what flights leave la guardia for san jose and arrive 10 pm
50
+ list the total number of flights to all airports by delta
51
+ can you tell me the time a flight would leave from atlanta to boston in the afternoon
52
+ show me the united airlines flights from denver to baltimore leaving on june fourteenth
53
+ please list all flights from dallas to philadelphia on monday
54
+ show me the flights from cleveland to memphis
55
+ please give me flights from atlanta to boston on wednesday and thursday
56
+ show me ground transportation in philadelphia on monday morning
57
+ what delta leaves boston for atlanta
58
+ find me the earliest boston departure and the latest atlanta return trip so that i can be on the ground the maximum amount of time in atlanta and return to boston on the same day
59
+ show me flights from boston to washington leaving july fifteen
60
+ i would like the time of your earliest flight in the morning from philadelphia to washington on american airlines
61
+ show me the flights from baltimore to boston
62
+ please list the flight schedule from baltimore to san francisco on friday nights
63
+ how long is a trip from philadelphia airport to downtown philadelphia
64
+ sure i'd like to determine what aircraft are use on july seventh leaving from boston and arriving in atlanta on july seventh
65
+ baltimore to philadelphia
66
+ what are the flights and fares from atlanta to philadelphia
67
+ united airlines flights stopping in denver
68
+ what flights are available wednesday afternoon from denver to san francisco
69
+ round trip fares from denver to philadelphia less than 1000 dollars
70
+ list the first class flights from baltimore to denver
71
+ what are the fares from newark to la monday and wednesday
72
+ what flights from chicago to kansas city
73
+ please show me flights from dallas to atlanta on monday
74
+ flights to baltimore
75
+ show me the latest flight to love field
76
+ how many of delta's night flights are first class
77
+ on united airlines give me the flight times from boston to dallas
78
+ show me the ground transportation schedule in philadelphia in the morning on wednesday
79
+ what is the last flight from boston to atlanta
80
+ what flights fly from denver to san francisco on monday tuesday wednesday thursday and friday
81
+ show me the flights from boston to philadelphia
82
+ i also need to go to san francisco on wednesday evening from dallas
83
+ from kansas city to salt lake city on delta arrive around 8 pm tomorrow
84
+ in new york i'll need to rent a car
85
+ show me flights from denver to boston on thursday
86
+ i would like to book a flight from charlotte to baltimore on april eighth
87
+ flights from oakland to san francisco on january twenty first 1992
88
+ how much is a limousine between dallas fort worth international airport and dallas
89
+ is there a flight from boston to san francisco making a stopover in dallas fort worth
90
+ what time are the flights from baltimore to san francisco
91
+ from las vegas to phoenix departing in the morning
92
+ how many passengers can a boeing 737 hold
93
+ i would like a flight that leaves on friday from philadelphia to dallas that makes a stop in atlanta
94
+ thank you for that information now i would like information on a flight on april sixteen from atlanta to philadelphia early in the morning
95
+ what time is the last flight from washington to san francisco
96
+ show me the least expensive flight leaving miami on sunday after 12 o'clock noon and arriving cleveland
97
+ what do you have tomorrow morning from pittsburgh to atlanta
98
+ how much is the cheapest flight from denver to pittsburgh
99
+ what is the cheapest one way fare from pittsburgh to atlanta traveling on tuesday august twentieth
100
+ show me the flights from denver to san diego leaving after 5 pm
101
+ what is the latest first class flight of the day leaving dallas for san francisco
102
+ show me a list of flights from pittsburgh to baltimore on august third
103
+ show morning flights from san francisco to pittsburgh
104
+ what are the flights from memphis to tacoma
105
+ can you list all nonstop flights between st. petersburg and charlotte that leave in the afternoon and arrive soon after 5 pm
106
+ show me all united flights from denver to san francisco for september first 1991
107
+ are there wednesday morning flights between pittsburgh and boston
108
+ list all american airlines from milwaukee to phoenix on saturday
109
+ give me the flights on december twenty seventh with the fares from indianapolis to orlando
110
+ okay all right do you have a flight on united airlines from atlanta to washington
111
+ show flights from denver to oakland arriving between 12 and 1 o'clock
112
+ list all nonstop flights on sunday from tampa to charlotte
113
+ i would like to make a one way flight from boston to atlanta
114
+ is there a flight in the afternoon from philadelphia that arrives in the evening in denver
115
+ what is the first flight from atlanta to baltimore that serves lunch
116
+ list list flights between oakland and denver
117
+ please give me a flight from boston to atlanta before 10 am in the morning
118
+ list the nonstop flights early tuesday morning from dallas to atlanta
119
+ what's the lowest round trip fare from denver to pittsburgh
120
+ please arrange a flight for me from denver to san francisco on us air
121
+ i would like to see information for flights from san francisco leaving after 12 pm to pittsburgh on monday
122
+ show me the cheapest flight from pittsburgh to atlanta on wednesday which leaves before noon and serves breakfast
123
+ what is the earliest flight from washington to san francisco
124
+ list flights from pittsburgh to los angeles which leave on thursday after 5 pm
125
+ list the flights from new york to miami on a tuesday which are nonstop and cost less than 466 dollars
126
+ list flights from denver to san francisco no denver to philadelphia
127
+ i need to find a plane from boston to san francisco on friday
128
+ what does lax stand for
129
+ show prices for all flights from baltimore to dallas on july twenty ninth
130
+ what flights are available from boston to washington late monday evening or early tuesday morning
131
+ what flights from washington dc to toronto
132
+ all flights from boston to washington dc on november eleventh before 10 am
133
+ list all flights from denver to philadelphia
134
+ i need a list of late afternoon flights from st. louis to chicago
135
+ show me the airlines for flights to or from love field
136
+ do you have any flights from chicago to indianapolis
137
+ what does yn stand for
138
+ shortest flights from nashville to st. petersburg
139
+ what are the fares for flights between atlanta and dfw
140
+ list the fares of midway airlines flights from boston to philadelphia
141
+ round trip fares from denver to philadelphia less than 1000 dollars
142
+ is there a continental flight leaving from las vegas to new york nonstop
143
+ i need the cost of a ticket going from denver to baltimore a first class ticket on united airlines
144
+ show me fares from philadelphia to san francisco on thursday morning
145
+ show me the round trip flights between phoenix and salt lake city
146
+ show me all the flights from denver to baltimore arriving may tenth
147
+ find the cheapest one way fare from boston to san francisco
148
+ show me the flights from boston to san francisco
149
+ please show me the flights from boston to san francisco
150
+ show me the airlines from love field
151
+ show business class fares on us air from boston to toronto
152
+ what is the latest flight leaving las vegas for ontario
153
+ flights from las vegas to phoenix
154
+ does flight ua 270 from denver to philadelphia have a meal
155
+ what nonstop flights are available from oakland to philadelphia arriving between 5 and 6 pm
156
+ give me the flights for american airline from philadelphia to dallas
157
+ show me the evening flights from atlanta to washington on wednesdays
158
+ i would like a coach class seat on a flight leaving denver arriving atlanta
159
+ can you list all the flights between phoenix and las vegas
160
+ show me the qx fare flights between atlanta and oakland on delta airlines
161
+ what afternoon flights are available between denver and dallas fort worth
162
+ fares and flights from pittsburgh to philadelphia
163
+ can you tell me what airline flies between denver and san francisco
164
+ how many flights does each airline have with booking class k
165
+ great now what i want to find out is on april twentieth from washington to denver do you have a flight least expensive fare around 5 o'clock in the morning
166
+ show me all direct flights from san francisco to boston departing before noon
167
+ i need a flight on thursday before 8 am from oakland to salt lake city
168
+ show me all the types of aircraft
169
+ i want a flight on continental from boston to san francisco
170
+ show flights from pittsburgh into san francisco
171
+ what city is mco
172
+ how many cities are served by american airline with first class flights
173
+ could you please show me all flights from charlotte to milwaukee
174
+ what flights depart san francisco after 4 pm and fly to washington via indianapolis
175
+ i would like to see the flights from denver to philadelphia
176
+ show me the flights that go from san diego to newark new jersey by way of houston
177
+ i would like information on flights from denver to san francisco after noon on wednesday
178
+ show me the flights from boston to pittsburgh
179
+ show me all flights from san diego to new york nonstop
180
+ show me the round trip tickets from baltimore to atlanta
181
+ show me the cheapest one way fares from san diego to miami
182
+ could you show me all weekday flights from phoenix to denver
183
+ i would like to fly from boston to philadelphia next thursday
184
+ i'm planning a trip to pittsburgh and i live in denver can you help me
185
+ i would like to find the least expensive flight from boston to denver
186
+ i would like to go from atlanta to denver on tuesday
187
+ atlanta to pittsburgh july twenty third
188
+ show me the flights from boston to atlanta
189
+ what airlines fly from burbank to denver
190
+ okay we're going from washington to denver first class ticket i'd like to know the cost of a first class ticket
191
+ i wish to book a flight from pittsburgh to atlanta coach discount fare
192
+ is it possible for me to fly from baltimore to san francisco
193
+ i want to fly from denver to san francisco with at least one stop
194
+ how many us air flights leave from washington
195
+ please list any flight available leaving oakland california tuesday arriving philadelphia wednesday
196
+ i'd like to find a flight from las vegas to detroit michigan that leaves in the afternoon on monday
197
+ are there any flights from denver to pittsburgh with stops in atlanta
198
+ i'd like to know the information from boston to philadelphia nonstop
199
+ show me all flights from denver to philadelphia on saturday after sunday which leave after noon
200
+ what are the flights from dallas to baltimore
201
+ do you have a flight from san francisco to atlanta around 8 am
202
+ what flights from seattle to salt lake city
203
+ what is the cheapest flight from boston to bwi
204
+ are there any flights from new york to los angeles which stop over in milwaukee
205
+ what is the earliest flight from oakland to washington dc on sunday
206
+ are there any turboprop flights from pittsburgh to baltimore on december seventeenth
207
+ show me the morning flights from boston to philadelphia
208
+ newark to cleveland daily
209
+ evening flights from philadelphia to oakland
210
+ show me prices and times for first class travel from baltimore to dallas next summer
211
+ what kind of plane flies from boston to pittsburgh after noon
212
+ i'd like to know what flights united airline has from dallas to san francisco
213
+ show me morning flights from toronto
214
+ what ground transportation is available at the boston airport
215
+ where do the flights from boston to oakland stop
216
+ show me the earliest flight from boston to san francisco
217
+ flights from la guardia or jfk to cleveland
218
+ find the cheapest one way fare from boston to san francisco
219
+ what are the flights from washington dc to denver
220
+ give me information on flights from atlanta to washington dc on wednesday after 4 pm and thursday before 9 am
221
+ flights between baltimore and washington dc
222
+ what fare codes cover flights from philadelphia to san francisco
223
+ are there any flights from boston to oakland that stop
224
+ list departure times from denver to philadelphia which are later than 10 o'clock and earlier than 2 pm
225
+ are there any airlines that have flights from boston to philadelphia that leave before 630 am
226
+ how many first class flights does united have today
227
+ please show me the flights available from san francisco to pittsburgh on tuesday
228
+ i'm in miami and i'd like to travel to las vegas on sunday
229
+ show me flights from denver to philadelphia
230
+ i would like to fly from pittsburgh to atlanta on us air at the latest time possible in the evening
231
+ show me all flights from dallas to pittsburgh which leave on monday after 8 o'clock am
232
+ are there any nonstop flights leaving from denver arriving in baltimore on july seventh
233
+ list round trip flights between boston and oakland using twa
234
+ what are the sunday flights from oakland to washington dc
235
+ what flights are there on sunday from seattle to minneapolis
236
+ what flights from las vegas to montreal on saturday
237
+ what is the fare on continental 271 from dallas to san francisco
238
+ show me flights denver to washington dc on thursday
239
+ what type of ground transportation is available at philadelphia airport
240
+ flights from phoenix to milwaukee on wednesday evening
241
+ show me the last flight from love field
242
+ can you list all flights that depart from orlando to kansas city
243
+ i want to fly from kansas city to chicago next wednesday arriving in the evening and returning the next day
244
+ what is the ground transportation available in the city of fort worth
245
+ i need a flight from baltimore to seattle that stops in minneapolis
246
+ what is the latest flight you have departing dallas to philadelphia
247
+ show me the flights from atlanta to philadelphia
248
+ show me the flights arriving at love field from other airports
249
+ what does ewr stand for
250
+ what flights from denver to salt lake city
251
+ please give me the flight times the morning on united airlines for september twentieth from philadelphia to san francisco
252
+ what is the earliest arrival in salt lake city of a flight from toronto
253
+ i'd like to see all the flights from boston to philadelphia
254
+ what is fare code c
255
+ what kind of aircraft does delta fly before 8 am on august second from boston to denver
256
+ flight from denver to san francisco in the afternoon
257
+ what is the first flight from boston to stapleton airport for tomorrow
258
+ i need to know what flights leave atlanta on sunday evening and arrive in baltimore
259
+ what are the flights from milwaukee to orlando on wednesday
260
+ what is the cheapest fare between denver and boston
261
+ what airlines have business class
262
+ i need a flight from san francisco to pittsburgh and then pittsburgh to new york and new york to san francisco
263
+ what flights are there between washington dc and san francisco leaving washington after 6 pm on wednesday
264
+ what type of aircraft does eastern fly from atlanta to denver before 6 pm
265
+ i would like the flights available from boston to denver arriving in denver on 9 o'clock wednesday morning on or by 9 o'clock wednesday morning
266
+ what ground transportation is available at the baltimore airport
267
+ show me flights from atlanta to baltimore denver and dallas
268
+ what flights are there from minneapolis to chicago
269
+ flights from denver to pittsburgh on thursday
270
+ may i have a list of flights going from boston to denver on the twenty ninth of july
271
+ what flights are there between nashville and st. louis which are nonstop and arrive after noon and before 8 pm
272
+ please list the flight times for boston to pittsburgh
273
+ flight leaving from oakland to salt lake city
274
+ what are the different classes that an airline offers
275
+ could you tell me if there is ground transportation between the boston airport and boston downtown
276
+ ground transportation denver
277
+ what are the prices of the flights from atlanta to dallas in the morning
278
+ how long does it take to fly from boston to atlanta
279
+ please list the friday afternoon flights from san jose to dallas on american airlines
280
+ is there an american airlines flight in the evening from dallas to san francisco
281
+ what ground transportation is available in denver
282
+ show me the fares from dallas to san francisco
283
+ in pittsburgh i'd like to rent a car
284
+ i would like to find a flight that goes from tampa to montreal making a stop in new york and a flight that serves lunch
285
+ please give me flights from atlanta to boston on wednesday afternoon and thursday morning
286
+ can you list all flights leaving from st. louis and arriving in milwaukee
287
+ flights from montreal to las vegas
288
+ give me the flights from chicago to seattle on saturday morning
289
+ what is airline nw
290
+ i need a flight tonight from charlotte to las vegas with a stop in st. louis and i want dinner
291
+ what's the latest flight out of denver that arrives in pittsburgh next monday
292
+ please list the flights taking off and landing on general mitchell international airport
293
+ what limousine service is in boston
294
+ what is fare code y mean
295
+ are there delta flights leaving denver
296
+ on thursday i'd like a flight from st. petersburg to miami
297
+ when do planes leave boston for
298
+ what flights are there wednesday morning from atlanta to philadelphia
299
+ show me all flights from san francisco to boston philadelphia or baltimore
300
+ what type of aircraft is used on the first flight from philadelphia to dallas in the morning
301
+ what are the flights from pittsburgh to oakland
302
+ list the morning flights at a 124 dollars from atlanta to boston
303
+ all flights from miami to new york
304
+ show flights from denver to oakland
305
+ show flights from philadelphia to san francisco
306
+ i'd like a flight tomorrow late from nashville to houston with dinner please
307
+ show me all prices of economy from baltimore to dallas
308
+ i need a flight from montreal quebec to san diego california leaving this sunday
309
+ show me the cheapest one way flight from san francisco to boston leaving san francisco after 9 pm
310
+ does united airlines have flights between boston and denver
311
+ i would like to fly us air from orlando to cleveland in the late evening what do you have available
312
+ what are the flights from milwaukee to orlando on wednesday night
313
+ show me the flights from newark to los angeles
314
+ can you give me the evening flight on wednesday from washington to atlanta again
315
+ what are the flights and prices from la to charlotte for monday morning
316
+ what first class flights are available on july twenty fifth 1991 from denver to baltimore
317
+ show me all flights from pittsburgh to baltimore tomorrow which serve a meal
318
+ show me all the flights between philadelphia and denver
319
+ flights from phoenix to newark
320
+ all flights from pittsburgh to dallas round trip after 12 pm less than 100
321
+ thanks and what's the last flight back from washington to boston
322
+ show me the flights from boston to baltimore
323
+ what does fare code q mean
324
+ show me the flights arriving in baltimore from philadelphia at about 4 o'clock
325
+ what is the cheapest fare from baltimore to dallas in any class
326
+ give me all nonstops from new york to vegas that arrive on a sunday
327
+ what is sa
328
+ show me the flights from boston to san francisco
329
+ what does fare code qo mean
330
+ i need information on flights leaving dallas arriving in boston leaving dallas early in the morning
331
+ what is the earliest flight on thursday from atlanta to washington dc
332
+ what flights are available saturday to san francisco from dallas
333
+ i'd like to fly from boston to san francisco
334
+ how many flights does american airlines have from boston to atlanta
335
+ does midwest express have any flights from montreal to nashville
336
+ show me all economy prices from dallas to baltimore
337
+ and how much does it cost to travel from boston airport to downtown
338
+ all flights before 10 am boston denver
339
+ show me the flights that go from san diego to newark with one stop in houston
340
+ show me the earliest flight on wednesday from baltimore to newark
341
+ i'd like to book the cheapest one way flight from pittsburgh to atlanta on july twentieth
342
+ what does mco mean
343
+ show me all the flights from charlotte to cleveland
344
+ do you have a flight from salt lake city to st. petersburg
345
+ what is the earliest flight from boston to atlanta
346
+ i'd like a flight tomorrow from kansas city to newark in the morning
347
+ show me all flights from boston to detroit
348
+ show me the flights arriving in baltimore on june fifteenth leaving either from denver or dallas
349
+ show me the flights from love field to other airports
350
+ what is the earliest flight i can get from baltimore to boston
351
+ what is the round trip thrift fare on us air from boston to san francisco
352
+ show me flights from los angeles to pittsburgh on monday evening
353
+ i would like a flight from atlanta to denver
354
+ give me all the flights from memphis to charlotte
355
+ from philadelphia to toronto
356
+ newark to cleveland
357
+ list all american airline flights which leave phoenix on wednesday and stop at milwaukee
358
+ show me all flights from pittsburgh to baltimore tomorrow
359
+ is there a direct flight from denver to pittsburgh in the morning of august thirty first that is nonstop
360
+ which airline offers the cheapest rate going from dallas to baltimore on july fourth
361
+ does midwest express serve charlotte
362
+ show me all the flights from philadelphia to san francisco
363
+ ground transportation in denver
364
+ show me all flights from boston to dallas fort worth both direct and connecting that arrive before noon
365
+ show flights from philadelphia to dallas on saturday
366
+ and flights leaving from atlanta to oakland leaving after 5 pm
367
+ okay and on may four i would like to go from atlanta to denver leaving early in the morning around 8
368
+ all flights from boston to washington dc on november eleventh
369
+ what are the early morning flights from boston to denver
370
+ what is the cheapest flight from denver to pittsburgh leaving on september twenty eighth
371
+ flight from dallas to oakland california on monday
372
+ i would like to fly from dallas to san francisco on saturday and arrive in san francisco before 4 pm
373
+ morning flights out of san francisco arriving boston afternoon
374
+ i'd like to see flights from baltimore to atlanta that arrive before noon
375
+ find me the earliest boston departure for atlanta and the lastest return trip from atlanta so that i can be in atlanta the longest amount of time but return to boston the same day
376
+ please give me the cheapest round trip airfare from atlanta to philadelphia on august the first
377
+ i would like information on flights from philadelphia to oakland california on friday afternoon
378
+ what afternoon flights are available from pittsburgh to atlanta on a weekday
379
+ show ground transportation in denver
380
+ please show me airlines with flights from denver to boston with stop in philadelphia
381
+ dallas to baltimore
382
+ rental cars in washington dc
383
+ does american airlines fly to san francisco from atlanta
384
+ kindly give me the type of aircraft used to fly from atlanta to denver
385
+ give me flights from denver to baltimore
386
+ what is fare class h
387
+ what is the earliest flight from washington to san francisco on friday that serves breakfast
388
+ what flights are there from atlanta to washington early on thursday mornings
389
+ what kind of ground transportation is there in dallas
390
+ could i have a list of flights in first class on monday from san francisco to pittsburgh starting at noon and afterwards
391
+ how much is a us air boston to pittsburgh daily nonstop flight
392
+ i'd like to go from boston to atlanta sometime after 5 pm can you tell me the flights that could do that for me
393
+ what's fare code yn
394
+ airports in new york
395
+ i'd like to arrange for two friends to fly into los angeles next saturday evening one of the people is coming from kansas city and the other is coming from las vegas
396
+ show me all overnight flights from washington dc to san francisco and list their fares
397
+ what ground transportation is there in atlanta
398
+ flights from pittsburgh to baltimore arriving between 4 and 5 pm
399
+ what does fare code qw mean
400
+ show flights from new york city to las vegas
401
+ i need information for ground transportation denver colorado
402
+ list the flight from philadelphia to san francisco on american airlines
403
+ show me the airlines for flights to or from love field
404
+ list nonstop flights from san francisco to oakland that depart in the afternoon
405
+ which airline serves denver pittsburgh and atlanta
406
+ how many first class flights does delta airlines have
407
+ please show flights arriving in philadelphia from denver
408
+ now show me the flights from pittsburgh to baltimore
409
+ show me flights from milwaukee to orlando on wednesday night or thursday morning
410
+ i would like to fly delta airlines from atlanta to pittsburgh
411
+ what is fare code f
412
+ what are the flights for united airlines on september twentieth in the morning
413
+ show all airlines with flights between denver and dallas
414
+ cheapest fare from nashville to seattle
415
+ how many flights does american airlines have with a class of service code f
416
+ find a nonstop flight between boston and washington arriving in washington around 5 pm
417
+ pittsburgh to baltimore please on january one
418
+ show me the costs and times for flights from san francisco to atlanta
419
+ what airlines fly from boston to denver
420
+ what ground transportation is there in atlanta
421
+ how far from the airport in the dallas fort worth airport is dallas
422
+ list all flights from tampa florida to miami that are the cheapest one way
423
+ show me the flights from philadelphia to baltimore
424
+ ground transportation in denver
425
+ please list all flights from atlanta to baltimore on wednesday and thursday
426
+ does flight dl 1083 from philadelphia to denver fly on saturdays
427
+ i would like to book a flight going from tampa to seattle on may twenty sixth i would like to stop in milwaukee on the way
428
+ i want to fly from boston to atlanta i would like the cheapest fare please
429
+ show me the flights from montreal to philly
430
+ what flights are available sunday afternoon from oakland to dallas
431
+ explain the restriction ap 80
432
+ i want to go from baltimore to san francisco with a stopover in denver
433
+ information on a flight from san francisco to philadelphia
434
+ shortest morning flights from cincinnati to tampa
435
+ what are the flights from boston to washington on october fifteenth 1991
436
+ what flights are there on wednesday evening from denver to sfo
437
+ show me a list of flights on american airlines from boston to dc on july twenty second
438
+ us air 269 leaving boston at 428 what is the arrival time in baltimore
439
+ i would like information on flights leaving early monday morning from atlanta to baltimore
440
+ now show me the flights from memphis to cleveland
441
+ what flights leave from nashville to phoenix
442
+ show me the air fare for the flights from baltimore to dallas
443
+ what are the flights from denver to san francisco
444
+ which airlines go from san francisco to washington by way of indianapolis
445
+ all flights from washington dc to san francisco on november twelfth
446
+ round trip fares from pittsburgh to philadelphia under 1000 dollars
447
+ show nonstop flights from new york to miami on a tuesday which cost less than 466 dollars one way
448
+ i'd like flights on american airlines from philadelphia to dallas arriving before 1145 am
449
+ show business class fares from san francisco to denver on united airlines
450
+ what is the earliest flight between logan and bwi
451
+ describe pittsburgh airport
452
+ show flights on us air from pittsburgh to oakland connecting through denver
453
+ list all nonstop flights on tuesday before noon from charlotte to baltimore
454
+ minneapolis to phoenix on monday
455
+ please list me the flights and their cost of all airlines flying from denver to baltimore
456
+ what airline uses the code hp
457
+ find a flight from san francisco to boston on wednesday
458
+ could you tell me about ground transportation arrangements from the dallas airport to downtown dallas
459
+ display all flights from pittsburgh to san francisco on august second
460
+ give me morning flights from charlotte to baltimore
461
+ anything from baltimore or washington with a stopover in denver going to san francisco
462
+ show me flights from boston to denver
463
+ show me the flights from columbus to charlotte
464
+ i need a flight from new york city to montreal thursday may six
465
+ philadelphia to san francisco
466
+ what is the earliest flight from boston to san francisco
467
+ is there a limousine service available from the pittsburgh airport
468
+ boston ground transportation
469
+ the earliest flight from boston to san francisco please that will be serving a meal
470
+ what does code qw mean
471
+ what airline is hp
472
+ what are the costs of car rental in dallas
473
+ show me the flights leaving saturday or sunday from milwaukee to phoenix
474
+ i'm interested in a flight from pittsburgh to atlanta
475
+ flights from kansas city to cleveland on wednesday
476
+ is there a nonstop flight from denver to san francisco
477
+ display all flights from san francisco to boston on august eighth
478
+ which airlines have flights between philadelphia and pittsburgh
479
+ i want to go from boston to atlanta on monday
480
+ what is the next flight from pittsburgh to san francisco after delta flight 1059
481
+ show me the least expensive flight from miami to cleveland on sunday after noon
482
+ what type of aircraft is used flying from atlanta to denver before 12 noon
483
+ show me all flights from boston to atlanta which leave atlanta after noon tomorrow
484
+ how much does it cost to rent a car in tacoma
485
+ what kind of airplane is flight ua 270 from denver to philadelphia
486
+ list all flights from boston to atlanta before 5 o'clock am on thursday
487
+ i'd like the earliest flight from dallas to boston
488
+ show me the flights on delta from atlanta in the morning
489
+ what flights from salt lake city to las vegas
490
+ show me the list of flights between philadelphia and denver that leave in the afternoon
491
+ what is the fare from atlanta to boston on coach one way
492
+ how many fares are there one way from tacoma to montreal
493
+ i would like to know some information on flights leaving philadelphia arriving in pittsburgh in the afternoon
494
+ what flights are available from pittsburgh to boston on wednesday of next week
495
+ is there a flight on continental airlines from boston to denver
496
+ pm flights dallas to atlanta
497
+ information on flights from baltimore to philadelphia
498
+ what flights from atlanta to st. louis on tuesday arriving around 230 pm
499
+ show me ground transportation in san francisco
500
+ what flights do you have from newark new jersey to ontario california that connect in phoenix
JointBERT-master/data/atis/dev/seq.out ADDED
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+ O B-airline_name O B-fromloc.city_name O B-toloc.city_name
58
+ O O O B-flight_mod B-fromloc.city_name O O O B-flight_mod B-fromloc.city_name O O O O O O O O O O O O O O O O B-toloc.city_name O O O B-toloc.city_name O O O B-return_date.date_relative
59
+ O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
60
+ O O O O B-flight_time O O B-flight_mod O O O B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name O B-airline_name I-airline_name
61
+ O O O O O B-fromloc.city_name O B-toloc.city_name
62
+ O O O B-flight_time I-flight_time O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day
63
+ O O O O O O B-fromloc.airport_name I-fromloc.airport_name O O B-toloc.city_name
64
+ O O O O O O O O O O B-depart_date.month_name B-depart_date.day_number O O B-fromloc.city_name O O O B-toloc.city_name O B-arrive_date.month_name B-arrive_date.day_number
65
+ B-fromloc.city_name O B-toloc.city_name
66
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name
67
+ B-airline_name I-airline_name O O O B-stoploc.city_name
68
+ O O O O B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
69
+ B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name B-cost_relative O B-fare_amount I-fare_amount
70
+ O O B-class_type I-class_type O O B-fromloc.city_name O B-toloc.city_name
71
+ O O O O O B-fromloc.city_name O B-toloc.city_name B-depart_date.day_name O B-depart_date.day_name
72
+ O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
73
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
74
+ O O B-toloc.city_name
75
+ O O O B-flight_mod O O B-toloc.airport_name I-toloc.airport_name
76
+ O O O B-airline_name B-depart_time.period_of_day O O B-class_type I-class_type
77
+ O B-airline_name I-airline_name O O O B-flight_time I-flight_time O B-fromloc.city_name O B-toloc.city_name
78
+ O O O O O O O B-city_name O O B-period_of_day O B-day_name
79
+ O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name
80
+ O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name B-depart_date.day_name B-depart_date.day_name B-depart_date.day_name O B-depart_date.day_name
81
+ O O O O O B-fromloc.city_name O B-toloc.city_name
82
+ O O O O O O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name
83
+ O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name O B-airline_name O B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time B-arrive_date.today_relative
84
+ O B-city_name I-city_name O O O O O B-transport_type
85
+ O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
86
+ O O O O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
87
+ O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number B-depart_date.year
88
+ O O O O B-transport_type O B-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name O B-toloc.city_name
89
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O O B-stoploc.city_name I-stoploc.city_name I-stoploc.city_name
90
+ O B-flight_time O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
91
+ O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O O B-depart_time.period_of_day
92
+ O O O O O O B-aircraft_code O
93
+ O O O O O O O O B-depart_date.day_name O B-fromloc.city_name O B-toloc.city_name O O O O O B-stoploc.city_name
94
+ O O O O O O O O O O O O O O B-depart_date.month_name B-depart_date.day_number O B-fromloc.city_name O B-toloc.city_name B-depart_time.period_mod O O B-depart_time.period_of_day
95
+ O B-flight_time O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
96
+ O O O B-cost_relative I-cost_relative O O B-fromloc.city_name O B-depart_date.day_name B-depart_time.time_relative B-depart_time.time I-depart_time.time I-depart_time.time O O B-toloc.city_name
97
+ O O O O B-depart_date.today_relative B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name
98
+ O O O O B-cost_relative O O B-fromloc.city_name O B-toloc.city_name
99
+ O O O B-cost_relative B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name O O B-depart_date.day_name B-depart_date.month_name B-depart_date.day_number
100
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_time.time_relative B-depart_time.time I-depart_time.time
101
+ O O O B-flight_mod B-class_type I-class_type O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
102
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
103
+ O B-depart_time.period_of_day O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
104
+ O O O O O B-fromloc.city_name O B-toloc.city_name
105
+ O O O O B-flight_stop O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O O O B-arrive_time.period_of_day O O O B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
106
+ O O O B-airline_name O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number B-depart_date.year
107
+ O O B-depart_date.day_name B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
108
+ O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
109
+ O O O O O B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number O O O O B-fromloc.city_name O B-toloc.city_name
110
+ O O O O O O O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name
111
+ O O O B-fromloc.city_name O B-toloc.city_name O O B-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
112
+ O O B-flight_stop O O B-arrive_date.day_name O B-fromloc.city_name O B-toloc.city_name
113
+ O O O O O O B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name
114
+ O O O O O O B-depart_time.period_of_day O B-fromloc.city_name O O O O B-arrive_time.period_of_day O B-toloc.city_name
115
+ O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name O O B-meal_description
116
+ O O O O B-fromloc.city_name O B-toloc.city_name
117
+ O O O O O O B-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.time I-depart_time.time O O B-depart_time.period_of_day
118
+ O O B-flight_stop O B-arrive_time.period_mod B-arrive_date.day_name B-arrive_time.period_of_day O B-fromloc.city_name O B-toloc.city_name
119
+ O O B-cost_relative B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name
120
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-airline_name I-airline_name
121
+ O O O O O O O O O B-fromloc.city_name I-fromloc.city_name O B-depart_time.time_relative B-depart_time.time I-depart_time.time O B-toloc.city_name O B-depart_date.day_name
122
+ O O O B-cost_relative O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name O O B-depart_time.time_relative B-depart_time.time O O B-meal_description
123
+ O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
124
+ O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O B-depart_date.day_name B-depart_time.time_relative B-depart_time.time I-depart_time.time
125
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O B-depart_date.day_name O O B-flight_stop O O B-cost_relative O B-fare_amount I-fare_amount
126
+ O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-fromloc.city_name O B-toloc.city_name
127
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name
128
+ O O B-airport_code O O
129
+ O O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number
130
+ O O O O O B-fromloc.city_name O B-toloc.city_name B-depart_time.period_mod B-depart_date.day_name B-depart_time.period_of_day B-or B-depart_time.period_mod B-depart_date.day_name B-depart_time.period_of_day
131
+ O O O B-fromloc.city_name B-fromloc.state_code O B-toloc.city_name
132
+ O O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code O B-depart_date.month_name B-depart_date.day_number B-depart_time.time_relative B-depart_time.time I-depart_time.time
133
+ O O O O B-fromloc.city_name O B-toloc.city_name
134
+ O O O O O B-depart_time.period_of_day I-depart_time.period_of_day O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
135
+ O O O O O O O O O B-fromloc.airport_name I-fromloc.airport_name
136
+ O O O O O O B-fromloc.city_name O B-toloc.city_name
137
+ O O B-fare_basis_code O O
138
+ B-flight_mod O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
139
+ O O O O O O O B-fromloc.city_name O B-toloc.airport_code
140
+ O O O O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name
141
+ B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name B-cost_relative O B-fare_amount I-fare_amount
142
+ O O O B-airline_name O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-flight_stop
143
+ O O O O O O O O O B-fromloc.city_name O B-toloc.city_name O B-class_type I-class_type O O B-airline_name I-airline_name
144
+ O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day
145
+ O O O B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
146
+ O O O O O O B-fromloc.city_name O B-toloc.city_name O B-arrive_date.month_name B-arrive_date.day_number
147
+ O O B-cost_relative B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
148
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
149
+ O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
150
+ O O O O O B-fromloc.airport_name I-fromloc.airport_name
151
+ O B-class_type I-class_type O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name
152
+ O O O B-flight_mod O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
153
+ O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
154
+ O O B-airline_code B-flight_number O B-fromloc.city_name O B-toloc.city_name O O B-meal
155
+ O B-flight_stop O O O O B-fromloc.city_name O B-toloc.city_name O O B-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
156
+ O O O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name
157
+ O O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
158
+ O O O O B-class_type I-class_type O O O O O B-fromloc.city_name O B-toloc.city_name
159
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
160
+ O O O B-fare_basis_code I-fare_basis_code O O B-fromloc.city_name O B-toloc.city_name O B-airline_name I-airline_name
161
+ O B-depart_time.period_of_day O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
162
+ O O O O B-fromloc.city_name O B-toloc.city_name
163
+ O O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
164
+ O O O O O O O O O O B-fare_basis_code
165
+ O O O O O O O O O O B-depart_date.month_name B-depart_date.day_number O B-fromloc.city_name O B-toloc.city_name O O O O O B-cost_relative I-cost_relative O B-depart_time.time_relative B-depart_time.time I-depart_time.time O O B-depart_time.period_of_day
166
+ O O O B-connect O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_time.time_relative B-depart_time.time
167
+ O O O O O B-depart_date.day_name B-depart_time.time_relative B-depart_time.time I-depart_time.time O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
168
+ O O O O O O O
169
+ O O O O O B-airline_name O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
170
+ O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
171
+ O O O B-airport_code
172
+ O O O O O O B-airline_name I-airline_name O B-class_type I-class_type O
173
+ O O O O O O O O B-fromloc.city_name O B-toloc.city_name
174
+ O O O B-fromloc.city_name I-fromloc.city_name B-depart_time.time_relative B-depart_time.time I-depart_time.time O O O B-toloc.city_name O B-stoploc.city_name
175
+ O O O O O O O O B-fromloc.city_name O B-toloc.city_name
176
+ O O O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-toloc.state_name I-toloc.state_name O O O B-stoploc.city_name
177
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-depart_time.time_relative B-depart_time.time O B-depart_date.day_name
178
+ O O O O O B-fromloc.city_name O B-toloc.city_name
179
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-flight_stop
180
+ O O O B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name
181
+ O O O B-cost_relative B-round_trip I-round_trip O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
182
+ O O O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name
183
+ O O O O O O B-fromloc.city_name O B-toloc.city_name B-depart_date.date_relative B-depart_date.day_name
184
+ O O O O O B-toloc.city_name O O O O B-fromloc.city_name O O O O
185
+ O O O O O O B-cost_relative I-cost_relative O O B-fromloc.city_name O B-toloc.city_name
186
+ O O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
187
+ B-fromloc.city_name O B-toloc.city_name B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number
188
+ O O O O O B-fromloc.city_name O B-toloc.city_name
189
+ O O O O B-fromloc.city_name O B-toloc.city_name
190
+ O O O O B-fromloc.city_name O B-toloc.city_name B-class_type I-class_type O O O O O O O O O B-class_type I-class_type O
191
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name B-class_type O O
192
+ O O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
193
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O B-flight_stop I-flight_stop
194
+ O O B-airline_name I-airline_name O O O B-fromloc.city_name
195
+ O O O O O O B-fromloc.city_name B-fromloc.state_name B-depart_date.day_name O B-toloc.city_name B-arrive_date.day_name
196
+ O O O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-toloc.state_name O O O O B-depart_time.period_of_day O B-depart_date.day_name
197
+ O O O O O B-fromloc.city_name O B-toloc.city_name O O O B-stoploc.city_name
198
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name B-flight_stop
199
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_date.date_relative B-depart_date.day_name O O B-depart_time.time_relative B-depart_time.time
200
+ O O O O O B-fromloc.city_name O B-toloc.city_name
201
+ O O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.time I-depart_time.time
202
+ O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
203
+ O O O B-cost_relative O O B-fromloc.city_name O B-toloc.airport_code
204
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O O B-stoploc.city_name
205
+ O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code O B-depart_date.day_name
206
+ O O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
207
+ O O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
208
+ B-fromloc.city_name O B-toloc.city_name B-flight_days
209
+ B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
210
+ O O O O B-flight_time O B-class_type I-class_type O O B-fromloc.city_name O B-toloc.city_name O O
211
+ O O O O O O B-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.time
212
+ O O O O O O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
213
+ O O B-depart_time.period_of_day O O B-fromloc.city_name
214
+ O O O O O O O B-airport_name I-airport_name
215
+ O O O O O B-fromloc.city_name O B-toloc.city_name B-flight_stop
216
+ O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
217
+ O O B-fromloc.airport_name I-fromloc.airport_name B-or B-fromloc.airport_code O B-toloc.city_name
218
+ O O B-cost_relative B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
219
+ O O O O O B-fromloc.city_name B-fromloc.state_code O B-toloc.city_name
220
+ O O O O O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code O B-depart_date.day_name B-depart_time.time_relative B-depart_time.time I-depart_time.time O B-depart_date.day_name B-depart_time.time_relative B-depart_time.time I-depart_time.time
221
+ O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code
222
+ O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
223
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-flight_stop
224
+ O B-flight_time I-flight_time O B-fromloc.city_name O B-toloc.city_name O O B-depart_time.time_relative O B-depart_time.time I-depart_time.time O B-depart_time.time_relative O B-depart_time.time I-depart_time.time
225
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226
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227
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228
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229
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230
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231
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232
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233
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234
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235
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236
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237
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238
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239
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240
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241
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242
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243
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244
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245
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246
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247
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248
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249
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250
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251
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252
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253
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254
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255
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256
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257
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258
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259
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260
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261
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262
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263
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264
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265
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266
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267
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268
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269
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270
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271
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272
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273
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274
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275
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276
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277
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278
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279
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280
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281
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282
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283
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284
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285
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286
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287
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288
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289
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290
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291
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292
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293
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294
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295
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296
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297
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298
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299
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300
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301
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302
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303
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304
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305
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306
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307
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308
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309
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310
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311
+ O O O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name O O B-depart_time.period_mod B-depart_time.period_of_day O O O O O
312
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313
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314
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315
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316
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317
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318
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319
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320
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321
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322
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323
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324
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325
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326
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327
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328
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329
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330
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331
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332
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333
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334
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335
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336
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337
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338
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339
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340
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341
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342
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343
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344
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345
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346
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347
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348
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349
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350
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351
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352
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353
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354
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355
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356
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357
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358
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359
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360
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361
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362
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363
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364
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365
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366
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367
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368
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369
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370
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371
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372
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373
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374
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375
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376
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377
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378
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379
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380
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381
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382
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383
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384
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385
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386
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387
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388
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389
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390
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391
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392
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393
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394
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395
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396
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397
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398
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399
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400
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401
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402
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403
+ O O O O O O O O O B-fromloc.airport_name I-fromloc.airport_name
404
+ O B-flight_stop O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O O O B-arrive_time.period_of_day
405
+ O O O B-fromloc.city_name B-fromloc.city_name O B-fromloc.city_name
406
+ O O B-class_type I-class_type O O B-airline_name I-airline_name O
407
+ O O O O O B-toloc.city_name O B-fromloc.city_name
408
+ O O O O O O B-fromloc.city_name O B-toloc.city_name
409
+ O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day B-or B-depart_date.day_name B-depart_time.period_of_day
410
+ O O O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name
411
+ O O O O B-fare_basis_code
412
+ O O O O O B-airline_name I-airline_name O B-depart_date.month_name B-depart_date.day_number O O B-depart_time.period_of_day
413
+ O O O O O O B-fromloc.city_name O B-toloc.city_name
414
+ B-cost_relative O O B-fromloc.city_name O B-toloc.city_name
415
+ O O O O B-airline_name I-airline_name O O O O O O O B-fare_basis_code
416
+ O O B-flight_stop O O B-fromloc.city_name O B-toloc.city_name O O B-toloc.city_name B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
417
+ B-fromloc.city_name O B-toloc.city_name O O B-depart_date.month_name B-depart_date.day_number
418
+ O O O O O B-flight_time O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
419
+ O O O O B-fromloc.city_name O B-toloc.city_name
420
+ O O O O O O B-city_name
421
+ O O O O O O O B-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name O B-fromloc.city_name
422
+ O O O O B-fromloc.city_name B-fromloc.state_name O B-toloc.city_name O O O B-cost_relative B-round_trip I-round_trip
423
+ O O O O O B-fromloc.city_name O B-toloc.city_name
424
+ O O O B-city_name
425
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name O B-depart_date.day_name
426
+ O O B-airline_code B-flight_number O B-fromloc.city_name O B-toloc.city_name O O B-depart_date.day_name
427
+ O O O O O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number O O O O O O B-stoploc.city_name O O O
428
+ O O O O O B-fromloc.city_name O B-toloc.city_name O O O O B-cost_relative O O
429
+ O O O O O B-fromloc.city_name O B-toloc.city_name
430
+ O O O O B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name
431
+ O O O B-restriction_code I-restriction_code
432
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O O B-stoploc.city_name
433
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
434
+ B-flight_mod B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
435
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number B-depart_date.year
436
+ O O O O O B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.airport_code
437
+ O O O O O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.state_code O B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number
438
+ B-airline_name I-airline_name B-flight_number O B-fromloc.city_name O B-depart_time.time O O O B-flight_time I-flight_time O B-toloc.city_name
439
+ O O O O O O O B-depart_time.period_mod B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name
440
+ O O O O O O B-fromloc.city_name O B-toloc.city_name
441
+ O O O O B-fromloc.city_name O B-toloc.city_name
442
+ O O O O O O O O O B-fromloc.city_name O B-toloc.city_name
443
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
444
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O O B-stoploc.city_name
445
+ O O O B-fromloc.city_name B-fromloc.state_code O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
446
+ B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name B-cost_relative B-fare_amount I-fare_amount
447
+ O B-flight_stop O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O B-arrive_date.day_name O O B-cost_relative O B-fare_amount I-fare_amount B-round_trip I-round_trip
448
+ O O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name O B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
449
+ O B-class_type I-class_type O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-airline_name I-airline_name
450
+ O O O B-flight_mod O O B-fromloc.airport_name O B-toloc.airport_code
451
+ O B-airport_name I-airport_name
452
+ O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name B-connect O B-stoploc.city_name
453
+ O O B-flight_stop O O B-arrive_date.day_name B-arrive_time.time_relative B-arrive_time.time O B-fromloc.city_name O B-toloc.city_name
454
+ B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
455
+ O O O O O O O O O O O O O B-fromloc.city_name O B-toloc.city_name
456
+ O O O O O B-airline_code
457
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
458
+ O O O O O O O O O O B-fromloc.airport_name I-fromloc.airport_name O O B-toloc.city_name
459
+ O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
460
+ O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
461
+ O O B-fromloc.city_name B-or B-fromloc.city_name O O O O B-stoploc.city_name O O B-toloc.city_name I-toloc.city_name
462
+ O O O O B-fromloc.city_name O B-toloc.city_name
463
+ O O O O O B-fromloc.city_name O B-toloc.city_name
464
+ O O O O O B-fromloc.city_name I-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_date.month_name B-depart_date.day_number
465
+ B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
466
+ O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
467
+ O O O B-transport_type O O O O B-fromloc.airport_name I-fromloc.airport_name
468
+ B-city_name O O
469
+ O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O O O O B-meal
470
+ O O O B-fare_basis_code O
471
+ O O O B-airline_code
472
+ O O O O O B-transport_type I-transport_type O B-city_name
473
+ O O O O O B-depart_date.day_name B-or B-depart_date.day_name O B-fromloc.city_name O B-toloc.city_name
474
+ O O O O O O B-fromloc.city_name O B-toloc.city_name
475
+ O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
476
+ O O O B-flight_stop O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
477
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
478
+ O O O O O B-fromloc.city_name O B-toloc.city_name
479
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
480
+ O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-mod B-airline_name O B-flight_number
481
+ O O O B-cost_relative I-cost_relative O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_time.time_relative B-depart_time.time
482
+ O O O O O O O O B-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.time I-depart_time.time
483
+ O O O O O B-fromloc.city_name O B-toloc.city_name O O B-fromloc.city_name B-depart_time.time_relative B-depart_time.time B-depart_date.today_relative
484
+ O O O O O O O O B-transport_type O B-city_name
485
+ O O O O O O B-airline_code B-flight_number O B-fromloc.city_name O B-toloc.city_name
486
+ O O O O B-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.time I-depart_time.time I-depart_time.time O B-depart_date.day_name
487
+ O O O B-flight_mod O O B-fromloc.city_name O B-toloc.city_name
488
+ O O O O O B-airline_name O B-fromloc.city_name O O B-depart_time.period_of_day
489
+ O O O B-fromloc.city_name I-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name
490
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name O O O O B-depart_time.period_of_day
491
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-class_type B-round_trip I-round_trip
492
+ O O O O O B-round_trip I-round_trip O B-fromloc.city_name O B-toloc.city_name
493
+ O O O O O O O O O O B-fromloc.city_name O O B-toloc.city_name O O B-arrive_time.period_of_day
494
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name O B-depart_date.date_relative O
495
+ O O O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name
496
+ B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name
497
+ O O O O B-fromloc.city_name O B-toloc.city_name
498
+ O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name O B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
499
+ O O O O O B-city_name I-city_name
500
+ O O O O O O B-fromloc.city_name B-fromloc.state_name I-fromloc.state_name O B-toloc.city_name B-toloc.state_name O B-connect O B-stoploc.city_name
JointBERT-master/data/atis/intent_label.txt ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ UNK
2
+ atis_abbreviation
3
+ atis_aircraft
4
+ atis_aircraft#atis_flight#atis_flight_no
5
+ atis_airfare
6
+ atis_airline
7
+ atis_airline#atis_flight_no
8
+ atis_airport
9
+ atis_capacity
10
+ atis_cheapest
11
+ atis_city
12
+ atis_distance
13
+ atis_flight
14
+ atis_flight#atis_airfare
15
+ atis_flight_no
16
+ atis_flight_time
17
+ atis_ground_fare
18
+ atis_ground_service
19
+ atis_ground_service#atis_ground_fare
20
+ atis_meal
21
+ atis_quantity
22
+ atis_restriction
JointBERT-master/data/atis/slot_label.txt ADDED
@@ -0,0 +1,122 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ PAD
2
+ UNK
3
+ O
4
+ B-aircraft_code
5
+ B-airline_code
6
+ B-airline_name
7
+ I-airline_name
8
+ B-airport_code
9
+ B-airport_name
10
+ I-airport_name
11
+ B-arrive_date.date_relative
12
+ B-arrive_date.day_name
13
+ B-arrive_date.day_number
14
+ I-arrive_date.day_number
15
+ B-arrive_date.month_name
16
+ B-arrive_date.today_relative
17
+ B-arrive_time.end_time
18
+ I-arrive_time.end_time
19
+ B-arrive_time.period_mod
20
+ B-arrive_time.period_of_day
21
+ I-arrive_time.period_of_day
22
+ B-arrive_time.start_time
23
+ I-arrive_time.start_time
24
+ B-arrive_time.time
25
+ I-arrive_time.time
26
+ B-arrive_time.time_relative
27
+ I-arrive_time.time_relative
28
+ B-city_name
29
+ I-city_name
30
+ B-class_type
31
+ I-class_type
32
+ B-connect
33
+ B-cost_relative
34
+ I-cost_relative
35
+ B-day_name
36
+ B-day_number
37
+ B-days_code
38
+ B-depart_date.date_relative
39
+ B-depart_date.day_name
40
+ B-depart_date.day_number
41
+ I-depart_date.day_number
42
+ B-depart_date.month_name
43
+ B-depart_date.today_relative
44
+ I-depart_date.today_relative
45
+ B-depart_date.year
46
+ B-depart_time.end_time
47
+ I-depart_time.end_time
48
+ B-depart_time.period_mod
49
+ B-depart_time.period_of_day
50
+ I-depart_time.period_of_day
51
+ B-depart_time.start_time
52
+ I-depart_time.start_time
53
+ B-depart_time.time
54
+ I-depart_time.time
55
+ B-depart_time.time_relative
56
+ I-depart_time.time_relative
57
+ B-economy
58
+ I-economy
59
+ B-fare_amount
60
+ I-fare_amount
61
+ B-fare_basis_code
62
+ I-fare_basis_code
63
+ B-flight_days
64
+ B-flight_mod
65
+ I-flight_mod
66
+ B-flight_number
67
+ B-flight_stop
68
+ I-flight_stop
69
+ B-flight_time
70
+ I-flight_time
71
+ B-fromloc.airport_code
72
+ B-fromloc.airport_name
73
+ I-fromloc.airport_name
74
+ B-fromloc.city_name
75
+ I-fromloc.city_name
76
+ B-fromloc.state_code
77
+ B-fromloc.state_name
78
+ I-fromloc.state_name
79
+ B-meal
80
+ B-meal_code
81
+ I-meal_code
82
+ B-meal_description
83
+ I-meal_description
84
+ B-mod
85
+ B-month_name
86
+ B-or
87
+ B-period_of_day
88
+ B-restriction_code
89
+ I-restriction_code
90
+ B-return_date.date_relative
91
+ I-return_date.date_relative
92
+ B-return_date.day_name
93
+ B-return_date.day_number
94
+ B-return_date.month_name
95
+ B-return_date.today_relative
96
+ I-return_date.today_relative
97
+ B-return_time.period_mod
98
+ B-return_time.period_of_day
99
+ B-round_trip
100
+ I-round_trip
101
+ B-state_code
102
+ B-state_name
103
+ B-stoploc.airport_name
104
+ B-stoploc.city_name
105
+ I-stoploc.city_name
106
+ B-stoploc.state_code
107
+ B-time
108
+ I-time
109
+ B-time_relative
110
+ B-today_relative
111
+ I-today_relative
112
+ B-toloc.airport_code
113
+ B-toloc.airport_name
114
+ I-toloc.airport_name
115
+ B-toloc.city_name
116
+ I-toloc.city_name
117
+ B-toloc.country_name
118
+ B-toloc.state_code
119
+ B-toloc.state_name
120
+ I-toloc.state_name
121
+ B-transport_type
122
+ I-transport_type
JointBERT-master/data/atis/test/label ADDED
@@ -0,0 +1,893 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ atis_flight
2
+ atis_airfare
3
+ atis_flight
4
+ atis_flight
5
+ atis_flight
6
+ atis_flight
7
+ atis_flight
8
+ atis_flight
9
+ atis_flight
10
+ atis_flight
11
+ atis_flight
12
+ atis_flight
13
+ atis_flight#atis_airfare
14
+ atis_flight
15
+ atis_flight
16
+ atis_flight
17
+ atis_flight
18
+ atis_flight
19
+ atis_flight
20
+ atis_flight
21
+ atis_flight
22
+ atis_flight
23
+ atis_flight
24
+ atis_flight
25
+ atis_flight
26
+ atis_flight
27
+ atis_flight
28
+ atis_flight
29
+ atis_flight
30
+ atis_flight
31
+ atis_flight
32
+ atis_flight
33
+ atis_ground_service
34
+ atis_flight
35
+ atis_day_name
36
+ atis_flight
37
+ atis_day_name
38
+ atis_flight
39
+ atis_flight
40
+ atis_flight
41
+ atis_flight
42
+ atis_flight
43
+ atis_flight
44
+ atis_flight
45
+ atis_flight
46
+ atis_flight
47
+ atis_flight
48
+ atis_flight
49
+ atis_flight
50
+ atis_flight
51
+ atis_meal
52
+ atis_meal
53
+ atis_flight
54
+ atis_flight
55
+ atis_flight
56
+ atis_flight
57
+ atis_flight
58
+ atis_flight
59
+ atis_flight
60
+ atis_flight
61
+ atis_flight
62
+ atis_flight
63
+ atis_flight
64
+ atis_flight
65
+ atis_flight
66
+ atis_flight
67
+ atis_flight
68
+ atis_flight
69
+ atis_flight
70
+ atis_flight
71
+ atis_flight
72
+ atis_flight
73
+ atis_flight
74
+ atis_flight
75
+ atis_flight
76
+ atis_flight
77
+ atis_flight
78
+ atis_flight
79
+ atis_flight
80
+ atis_flight
81
+ atis_flight
82
+ atis_flight
83
+ atis_flight
84
+ atis_flight
85
+ atis_flight
86
+ atis_flight
87
+ atis_flight
88
+ atis_flight
89
+ atis_flight
90
+ atis_flight
91
+ atis_flight
92
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1
+ i would like to find a flight from charlotte to las vegas that makes a stop in st. louis
2
+ on april first i need a ticket from tacoma to san jose departing before 7 am
3
+ on april first i need a flight going from phoenix to san diego
4
+ i would like a flight traveling one way from phoenix to san diego on april first
5
+ i would like a flight from orlando to salt lake city for april first on delta airlines
6
+ i need a flight from toronto to newark one way leaving wednesday evening or thursday morning
7
+ monday morning i would like to fly from columbus to indianapolis
8
+ on wednesday april sixth i would like to fly from long beach to columbus after 3 pm
9
+ after 12 pm on wednesday april sixth i would like to fly from long beach to columbus
10
+ are there any flights from long beach to columbus on wednesday april sixth
11
+ find a flight from memphis to tacoma dinner
12
+ on next wednesday flight from kansas city to chicago should arrive in chicago around 7 pm return flight on thursday
13
+ show flight and prices kansas city to chicago on next wednesday arriving in chicago by 7 pm
14
+ flight on american from miami to chicago arrive in chicago about 5 pm
15
+ find flights arriving new york city next saturday
16
+ find nonstop flights from salt lake city to new york on saturday april ninth
17
+ show flights from burbank to milwaukee for today
18
+ show flights tomorrow evening from milwaukee to st. louis
19
+ show flights saturday evening from st. louis to burbank
20
+ show flights from burbank to st. louis on monday
21
+ show flights from burbank to milwaukee on monday
22
+ show flights tuesday evening from milwaukee to st. louis
23
+ show flights wednesday evening from st. louis to burbank
24
+ which flights travel from kansas city to los angeles
25
+ what flights travel from las vegas to los angeles
26
+ which flights travel from kansas city to los angeles on april ninth
27
+ which flights travel from las vegas to los angeles california and arrive on april ninth between 4 and 5 pm
28
+ which flights on us air go from orlando to cleveland
29
+ which flights travel from cleveland to indianapolis on april fifth
30
+ which flights travel from indianapolis to san diego on april fifth
31
+ which flights go from cleveland to indianapolis on april fifth
32
+ which flights travel from nashville to tacoma
33
+ does tacoma airport offer transportation from the airport to the downtown area
34
+ which flights travel from tacoma to san jose
35
+ what day of the week do flights from nashville to tacoma fly on
36
+ what are the flights from tacoma to san jose
37
+ what days of the week do flights from san jose to nashville fly on
38
+ what are the flights from tacoma to san jose
39
+ i need a flight that goes from boston to orlando
40
+ are there any flights from boston to orlando connecting in new york
41
+ are there any flights from boston to orlando connecting in columbus
42
+ does this flight serve dinner
43
+ i need a flight from charlotte to miami
44
+ i need a nonstop flight from miami to toronto
45
+ i need a nonstop flight from toronto to st. louis
46
+ i need a flight from toronto to st. louis
47
+ i need a flight from st. louis to charlotte
48
+ i need a flight on united airlines from la guardia to san jose
49
+ i need a flight from tampa to milwaukee
50
+ i need a flight from milwaukee to seattle
51
+ what meals are served on american flight 811 from tampa to milwaukee
52
+ what meals are served on american flight 665 673 from milwaukee to seattle
53
+ i need a flight from memphis to las vegas
54
+ i need a flight from las vegas to ontario
55
+ i need a flight from ontario to memphis
56
+ which flights go from milwaukee to tampa and stop in nashville
57
+ which flights leave newark after noon next saturday and arrive in los angeles
58
+ which flights leave detroit and arrive at st. petersburg around 9 am
59
+ which flights on northwest airline leave detroit and arrive at st. petersburg
60
+ which flights leave chicago next tuesday and arrive in detroit around 6 pm
61
+ show me round trip flights from chicago to detroit leaving next tuesday and returning the day after
62
+ which round trip flights leave chicago next tuesday around 6 pm and arrive in detroit
63
+ which round trip flights leave chicago next tuesday and arrive in detroit around 6 pm
64
+ which flights leave on monday from montreal and arrive in chicago in the morning
65
+ which flights leave chicago on april twelfth and arrive in indianapolis in the morning
66
+ which flights leave on wednesday april thirteenth from indianapolis and arrive in montreal in the morning
67
+ which flights leave april twelfth from indianapolis and arrive in montreal around 10 pm
68
+ i'd like to go from long beach to st. louis and i'd like to stop in dallas i'd also like to have lunch during my flight
69
+ next wednesday i would like to leave kansas city on a trip to chicago which arrives in chicago around 7 pm
70
+ i would like to return from chicago around 7 pm to kansas city
71
+ i would like to leave this afternoon on an american flight from cincinnati to burbank
72
+ on sunday evening i would like to leave montreal quebec on a flight to san diego california
73
+ what are the flights on sunday from montreal quebec to san diego california
74
+ on tuesday are the flights from san diego california to indianapolis indiana i would like the flight to be in the afternoon
75
+ on thursday morning i would like a nonstop flight from indianapolis to toronto
76
+ on friday morning i would like to fly from toronto to montreal
77
+ i would like an early morning flight today from los angeles to charlotte
78
+ on wednesday night i would like a flight from charlotte to newark
79
+ on friday night i would like a flight from newark to los angeles
80
+ find a flight from tampa to montreal by way of new york
81
+ please find a flight from miami florida to las vegas nevada arriving before 4 o'clock pm
82
+ please find a flight from las vegas to michigan
83
+ please find a flight from detroit michigan to st. petersburg arriving before 10 pm
84
+ please find a flight from st. petersburg to miami on thursday
85
+ please find a flight from san diego to toronto on alaska airlines
86
+ please find the flights from columbus to houston with a layover in nashville tomorrow
87
+ please give me the flights from nashville to houston nonstop with dinner served
88
+ please find flights available from kansas city to newark
89
+ please find a flight that goes from kansas city to newark to orlando back to kansas city
90
+ please find a flight from kansas city to newark
91
+ please find a flight from newark to orlando
92
+ please find a flight from orlando to kansas city
93
+ i would like to fly from columbus to phoenix through cincinnati in the afternoon
94
+ i would like to know what airports are in los angeles
95
+ does the airport at burbank have a flight that comes in from kansas city
96
+ which flights arrive in burbank from kansas city on saturdays in the afternoon
97
+ which flights arrive in burbank from las vegas on saturday april twenty third in the afternoon
98
+ which flights are available from orlando to cleveland that arrive around 10 pm
99
+ what flights are available from indianapolis to san diego on april twenty first in the late afternoon
100
+ what flights leave cleveland going to indianapolis on april twenty first in the morning
101
+ which flights are available on april twenty first in the morning from nashville to tacoma
102
+ which flights are available from tacoma to san jose in the morning on april twenty second
103
+ which flights are available from san jose to nashville leaving in the morning on april twenty three
104
+ what is the most expensive one way fare between detroit and westchester county
105
+ what airlines fly between detroit and westchester county
106
+ what are the departure times from detroit to westchester county
107
+ what is the latest flight from baltimore to oakland that serves dinner
108
+ what is the earliest flight between baltimore and oakland that serves breakfast
109
+ to what cities from boston does america west fly first class
110
+ what airline flies from boston to san diego
111
+ what is the latest breakfast flight from dallas to tampa
112
+ show me all lufthansa flights from seattle to boston with stopovers in minneapolis
113
+ show me all flights from seattle to boston with stopovers in minneapolis
114
+ list philadelphia to san francisco flights with stopovers in dallas
115
+ show me the connecting flights between boston and denver and the types of aircraft used
116
+ show me all the morning flights from philadelphia to fort worth
117
+ show me all the flights from kansas city to st. paul
118
+ show me northwest flight 608 from kansas city to st. paul
119
+ show me all the flights from indianapolis to charlotte on monday
120
+ what is the ground transportation between the charlotte airport charlotte airport and downtown charlotte
121
+ show me all the flights from charlotte to minneapolis that leave at 2 pm or later on monday
122
+ show me all the flights from charlotte to minneapolis on tuesday morning
123
+ show me the direct flights from charlotte to minneapolis on tuesday morning
124
+ show me flight us 1500 on monday from charlotte to minneapolis please
125
+ show me all the flights from minneapolis to indianapolis on tuesday that leave after 2 pm
126
+ show me the flights from minneapolis to indiana
127
+ show me the flights in from minneapolis to indianapolis on tuesday afternoon
128
+ show me flight us 1207 from indianapolis to charlotte on monday and flight us 1500 from charlotte to minneapolis on monday and flight twa 639 from minneapolis to indianapolis
129
+ show me all the flights from las vegas to new york city
130
+ which different airlines go from las vegas to new york city
131
+ show me all the flights on america west and twa from las vegas to jfk on a friday
132
+ what are the flights from tacoma to miami that leave after 6 pm tomorrow
133
+ i'd like to fly from san diego to houston on june tenth
134
+ is there an american airlines flight from houston to newark on june tenth after 6 pm
135
+ is there an american airlines flight from houston to newark on june tenth after 3 pm
136
+ i need to get from cincinnati to denver on june sixth by 6 pm
137
+ what's the ground transportation in denver
138
+ what's the fare for a taxi to denver
139
+ what are the fares for ground transportation in denver
140
+ i need to fly from denver to westchester county on june seventh after 3 pm
141
+ what's the ground transportation in westchester county
142
+ i need to take a united airlines flight on june eighth from westchester county to cincinnati after 3 pm
143
+ what united airlines flights on june eighth go from westchester county to cincinnati
144
+ on june eighth what flights go from westchester county to cincinnati
145
+ does us air fly from cincinnati to denver on june sixth
146
+ list the flights from cincinnati to denver on june sixth
147
+ list the flights from denver to westchester county on june seventh
148
+ list the flights from westchester county to cincinnati on june eighth
149
+ list the flights from cincinnati to westchester county on june sixth
150
+ list the flights from westchester county to denver on june seventh
151
+ list the flights from denver to cincinnati on june eighth
152
+ list the flights from denver to cincinnati on june sixth after 4 pm
153
+ list the flights from cincinnati to westchester county on june seventh
154
+ list the flights from westchester county to cincinnati on june seventh leaving after 5 pm
155
+ what airlines off from love field between 6 and 10 am on june sixth
156
+ what flights arrive at love field on june sixth
157
+ list the flights from montreal to philly before 9 am
158
+ list the flights from cleveland to memphis
159
+ list the flights from memphis to cleveland
160
+ list the flights from denver to baltimore arriving on july first
161
+ list the flights from dallas to baltimore arriving july first
162
+ list the flights from pittsburgh to baltimore arriving on july first
163
+ list the flights on canadian airlines international
164
+ how many canadian airlines international flights use j31
165
+ how many canadian airlines international flights use aircraft 320
166
+ how many canadian airlines flights use aircraft dh8
167
+ show me the flights on american airlines which fly from st. petersburg to ontario canada with a stopover in st. louis
168
+ show me the flights on american airlines which go from st. petersburg to ontario california by way of st. louis
169
+ which airport is closest to ontario california
170
+ show me the flights from houston to orlando
171
+ show me the flights from orlando to houston
172
+ show me the flights from detroit to las vegas
173
+ show me the cheapest round trip coach fare from las vegas to detroit
174
+ show me the cheapest round trip coach fare on twa from las vegas to detroit
175
+ show me the delta flights which serve a snack to coach passengers
176
+ what is meal code sb
177
+ what meals are available on dl 468 which al arrives in san francisco at 950 am
178
+ show me the delta flights from tampa to san francisco
179
+ show me delta flight 486
180
+ list the tower air flights on mondays
181
+ list all tower air flights with meals
182
+ what flights depart from baltimore
183
+ what flights depart from baltimore and arrive at san francisco on a friday
184
+ what flights leave from cincinnati in the morning and arrive in tampa
185
+ which flights depart from tampa and arrive in cincinnati in the evening
186
+ which flights depart from tampa in the early evening and arrive in cincinnati
187
+ which flights depart from philadelphia and arrive in atlanta
188
+ which flights depart from a atlanta and arrive in toronto
189
+ which flights depart from toronto and arrive in washington dc
190
+ which flights depart from new york and arrive in los angeles after 10 am
191
+ how far is new york's la guardia from downtown
192
+ how far is toronto international from downtown
193
+ how far is los angeles international from downtown
194
+ how far is san francisco international from downtown
195
+ how much is the limousine service in boston
196
+ how much is a limousine service in la guardia
197
+ how much is a limousine service in toronto international
198
+ how much is limousine service in los angeles
199
+ what airlines fly between washington dc and columbus ohio
200
+ what flights are there between washington dc and columbus ohio
201
+ what are the flights between washington dc and columbus ohio
202
+ what are the fares for all flights between washington and columbus
203
+ at the charlotte airport how many different types of aircraft are there for us air
204
+ list all us air flights arriving in charlotte on saturday at 1 pm
205
+ what is the first class round trip airfare from india indianapolis to memphis
206
+ list all flights from memphis to miami
207
+ list all flights and their fares from indianapolis to memphis on a monday morning
208
+ list all flights and their fares from memphis to miami on a wednesday evening
209
+ list all flights and their fares for all flights between miami and indianapolis
210
+ list all flights from cleveland to kansas city on monday
211
+ list all flights from kansas city to cleveland
212
+ list all flights from cleveland to nashville
213
+ list all flights from nashville to cleveland on sunday
214
+ list all sunday flights from cleveland to nashville and their fares
215
+ what airlines are departing from baltimore
216
+ which airlines fly from baltimore to san francisco
217
+ how long does a flight from baltimore to san francisco take
218
+ which flights are leaving from kansas city to atlanta early monday morning
219
+ which flights are leaving atlanta and arriving in st. louis close to 230 pm on tuesday
220
+ please list flights from st. louis to st. paul which depart after 10 am thursday morning
221
+ list flights from st. paul to kansas city friday in the evening with a meal included
222
+ list early morning flights from cincinnati to tampa
223
+ list early evening flights from tampa to cincinnati
224
+ list evening flights from tampa to cincinnati
225
+ list flights from philadelphia to atlanta friday am
226
+ list flights from atlanta to toronto friday afternoon
227
+ list flights from toronto to washington dc saturday am
228
+ list flights from washington dc to philadelphia saturday pm
229
+ list direct flights from new york city to los angeles after 10 am
230
+ list the airfare for american airlines flight 19 from jfk to lax
231
+ what is fare code m
232
+ list the distance in miles from boston airport to downtown boston
233
+ list the distance in miles from new york's la guardia airport to downtown new york city
234
+ list the distance in miles from toronto international airport to downtown toronto
235
+ list the distance in miles from san francisco international airport to san francisco downtown
236
+ list limousine rates for the city of boston
237
+ list american airlines flights from houston to milwaukee departing friday pm
238
+ list flights from houston to milwaukee friday pm
239
+ list american airlines flights from milwaukee to san jose wednesday
240
+ list american airlines flights from san jose to dallas friday afternoon
241
+ list flights from dallas to houston arriving sunday afternoon
242
+ list airlines flying from seattle to salt lake city
243
+ what is the seating capacity for aircraft l10
244
+ what is the seating capacity for delta be1
245
+ list flights from seattle to salt lake city on delta l10
246
+ list flights from seattle to salt lake city on delta be1
247
+ list flights from boston to pittsburgh daily
248
+ list flights from pittsburgh to newark daily
249
+ list flights from newark to boston daily
250
+ list us air flights leaving saturday from charlotte airport at 1 pm
251
+ list us air flights leaving saturday from charlotte airport around 1 pm
252
+ list first class airfare round trip from indianapolis to memphis
253
+ what is fare code f
254
+ list flights from memphis to miami wednesday evening
255
+ list flights from miami to indianapolis sunday
256
+ list flights from ontario california to orlando florida
257
+ list flights from ontario california to salt lake city utah
258
+ list flights from ontario california to salt lake city utah monday
259
+ list flights from salt lake city utah to phoenix arizona monday
260
+ list flights from salt lake city to phoenix arizona tuesday
261
+ list flights from phoenix arizona to ontario california wednesday
262
+ what airlines fly from baltimore to san francisco
263
+ what is the fare for a first class round trip ticket from detroit to st. petersburg
264
+ what is the airfare for a round trip first class ticket from detroit to st. petersburg
265
+ kansas city to atlanta monday morning flights
266
+ monday morning flights from atlanta to kansas city
267
+ kansas city to atlanta monday morning flights
268
+ atlanta to st. louis tuesday before 230 pm flights
269
+ st. louis to st. paul thursday after 10 am
270
+ st. paul to kansas city friday night
271
+ cleveland to kansas city arrive monday before 3 pm
272
+ kansas city to cleveland flight arrive wednesday before 5 pm
273
+ cleveland to nashville flight friday morning
274
+ nashville to cleveland sunday before 9
275
+ first class flights pittsburgh to newark monday morning
276
+ flights newark to los angeles wednesday morning
277
+ los angeles to minneapolis thursday afternoon
278
+ minneapolis to pittsburgh flight
279
+ minneapolis to pittsburgh first class flight
280
+ i would like flights leaving from milwaukee to orlando
281
+ what does hp stand for
282
+ i would like flights from ontario to tacoma
283
+ i would like flights from minneapolis to san diego
284
+ i would like flights from salt lake city to cincinnati
285
+ i would like to see flights from cincinnati to salt lake city
286
+ i'd like flights from new york to miami
287
+ i would like flights from miami to new york
288
+ i would like a flight leaving san francisco for san diego
289
+ i would like flights from san diego to las vegas
290
+ i would like a flight from san diego to las vegas
291
+ i would like flights from las vegas to san francisco
292
+ what does fare code bn mean
293
+ i would like to have the airline that flies toronto detroit and st. louis
294
+ i would like a flight from toronto to detroit
295
+ i would like a flight from detroit to st. louis
296
+ i would like a flight from toronto to st. louis
297
+ i would like flights from san francisco to long beach
298
+ i would like flights leaving san francisco to san diego
299
+ i would like a flight from san francisco to st. petersburg
300
+ show me a one way flight from milwaukee to orlando leaving wednesday afternoon after 6 pm
301
+ show me one way flights from milwaukee to orlando on wednesday
302
+ show me flights from columbus to chicago first class that leave before 10 am
303
+ show me the cheapest round trip between st. petersburg and detroit that arrives before 7 pm
304
+ show me nonstop flights from kansas city to phoenix
305
+ what is airline wn
306
+ show me the cheapest first class round trip from new york to miami
307
+ now show me all the round trips from new york to miami
308
+ show me the cheapest one way flight from san francisco to houston
309
+ now show me the cheapest one way flight from houston to boston
310
+ show me the cheapest round trip fares from houston to boston
311
+ show me the cheapest round trip fares from san francisco to houston
312
+ show me the cheapest round trip fare from san francisco to houston on february twenty eighth 1994
313
+ show me the cheapest one way fare from san francisco to houston on february twenty eighth 1994
314
+ now show me ground transportation in houston on monday afternoon
315
+ now show me one way flights from houston to boston
316
+ and now show me ground transportation that i could get in boston late night
317
+ show me airlines that have flights between toronto and detroit between detroit and st. louis and between st. louis and toronto
318
+ show me round trip fares from toronto to detroit on delta northwest us air and united airlines
319
+ show me flights between detroit and st. louis on delta northwest us air and united airlines
320
+ show me flights from montreal to orlando and long beach
321
+ show me flights from montreal to orlando
322
+ i need a flight on friday afternoon in june from new york to cleveland
323
+ i need a flight from new york to los angeles on saturday evening on us air
324
+ i'd like a red eye flight from new york to los angeles on saturday evening on us air
325
+ i'd like a flight from new york to los angeles on saturday morning on us air
326
+ i need a flight from san francisco to milwaukee on monday morning
327
+ what does ua mean
328
+ i need a flight from milwaukee to washington dc on monday night
329
+ how about flights from milwaukee to washington dc on tuesday mornings
330
+ what meals are there on flight 382 from milwaukee to washington dc on tuesday morning
331
+ i'll need to rent a car in washington dc
332
+ can i get a flight on tuesday night from washington dc to oakland
333
+ how about from dc to oakland on wednesday morning
334
+ how much does it cost to fly on twa from columbus to milwaukee
335
+ what does q mean
336
+ how much does it cost to fly from columbus to st. louis round trip on twa
337
+ what's the cheapest flight from columbus to st. louis round trip on twa
338
+ what's the cheapest round trip flight on twa from columbus to st. paul
339
+ i want to fly from milwaukee to los angeles
340
+ can i get the shortest flight from milwaukee to orlando
341
+ what is the shortest flight from milwaukee to long beach
342
+ what does m mean
343
+ what does ap 57 mean
344
+ what is the shortest flight from milwaukee to st. petersburg
345
+ what is the shortest flight from milwaukee to long beach
346
+ what is the shortest flight from milwaukee to san diego
347
+ what does ap 20 mean
348
+ can i get a flight today from san francisco to detroit michigan
349
+ what's the cheapest flight from san francisco to detroit today
350
+ i want to fly from san francisco to milwaukee and from milwaukee to denver
351
+ what's the cheapest flight from san francisco to milwaukee
352
+ i need to rent a car in milwaukee
353
+ what's the cheapest flight tomorrow from milwaukee to denver
354
+ what ground transportation is available at denver
355
+ what's the cheapest flight from san francisco to denver
356
+ what flights leave from cleveland and go to dallas
357
+ show me all nonstop flights from st. petersburg to charlotte
358
+ what airline is us
359
+ show me flights between toronto and san diego
360
+ what is phl
361
+ what is mci
362
+ show me the flights between oakland and salt lake city
363
+ what does not sa mean
364
+ what is the earliest daily flight between oakland and salt lake city
365
+ what airline is dl
366
+ what is the latest daily flight between oakland and salt lake city
367
+ show me the flights between los angeles and dallas
368
+ what ground transportation is available from dallas fort worth airport to downtown dallas
369
+ how many passengers can an l1011 aircraft hold
370
+ what is the seating capacity of a dc9
371
+ what are the flights between dallas and phoenix
372
+ what ground transportation is available between phoenix airport and downtown phoenix
373
+ what is the seating capacity for the aircraft m80
374
+ are there any flights between dallas and phoenix using a dc10 aircraft
375
+ what airline is aa
376
+ show me the flights between milwaukee and indiana
377
+ what are the flights between milwaukee and pittsburgh
378
+ what ground transportation is available between pittsburgh airport and downtown pittsburgh
379
+ show me the flights between pittsburgh and washington dc
380
+ what ground transportation is available between dca and downtown washington
381
+ what are the flights between dca and milwaukee
382
+ what ground transportation is available between milwaukee airport and downtown milwaukee
383
+ determine the type of aircraft used on a flight from cleveland to dallas that leaves before noon
384
+ find a flight between st. petersburg and charlotte the flight should leave in the afternoon and arrive as soon after 5 pm as possible it should be a nonstop flight
385
+ list a flight on delta airlines from toronto to san diego
386
+ list a flight on american airlines from toronto to san diego
387
+ list a flight from toronto to san diego
388
+ list flights from oakland to salt lake city leaving after 1700 wednesday
389
+ list flights from oakland to salt lake city leaving after midnight thursday
390
+ list flights between phoenix and las vegas
391
+ list flights from las vegas to denver
392
+ list flights from milwaukee to washington dc before 1200
393
+ list flights from washington dc to pittsburgh leaving after 1800
394
+ list flights from washington dc to pittsburgh
395
+ list flights between pittsburgh and milwaukee
396
+ i'd like a flight to san diego from washington dc
397
+ i'd like to fly from cleveland to dallas
398
+ i want to fly from washington dc to phoenix arizona
399
+ i need a flight from phoenix to atlanta
400
+ i would like to fly from atlanta to san diego
401
+ i would like to fly from san diego to seattle
402
+ i would like to fly from orlando to kansas city
403
+ i need a flight from kansas city to minneapolis
404
+ i need a flight from san diego to washington dc
405
+ i need a flight from washington dc to san diego
406
+ i need a round trip flight from san diego to washington dc and the fares
407
+ i need a round trip from atlanta to washington dc and the fares leaving in the morning
408
+ i need a round trip from phoenix to washington dc and the fare leaving in the morning
409
+ what is the lowest fare for a flight from washington dc to boston
410
+ what is the lowest fare from washington dc to montreal
411
+ what is the lowest fare from toronto to washington dc
412
+ i want a flight from montreal to washington dc
413
+ i want a flight from nashville to seattle that arrives no later than 3 pm
414
+ i want a flight from memphis to seattle that arrives no later than 3 pm
415
+ i need a flight from indianapolis to seattle arriving in seattle at 1205 pm
416
+ i want a flight round trip from memphis to seattle
417
+ i want to fly from nashville to seattle and i want the cheapest fare round trip
418
+ i want to fly from memphis to seattle round trip with the cheapest fare
419
+ i want to fly from indianapolis to seattle round trip with the cheapest fare
420
+ please list flights from orlando to philadelphia
421
+ please list flights from san francisco to charlotte
422
+ please list flights from milwaukee to philadelphia
423
+ please list flights from philadelphia to san francisco
424
+ please show ground transportation to milwaukee
425
+ please list flights from san francisco to milwaukee
426
+ list flights from houston to denver
427
+ list flights from houston to phoenix
428
+ list flights from phoenix to houston
429
+ list flights from newark to houston
430
+ show flights from denver to houston
431
+ show flights from st. petersburg to charlotte
432
+ show flights from orlando to kansas city
433
+ show flights from kansas city to minneapolis
434
+ show flights from kansas city to orlando
435
+ show flights from minneapolis to kansas city
436
+ show flights from kansas city to orlando
437
+ list flights from washington dc to boston
438
+ list fares from washington dc to montreal
439
+ list flights from washington dc to montreal
440
+ list fares from washington dc to toronto that should be good
441
+ list fares from washington dc to boston
442
+ list flights from washington dc to montreal
443
+ list flights from washington dc to toronto
444
+ list flights from toronto to washington dc
445
+ list flights from oakland to salt lake city
446
+ what flights go from dallas to phoenix
447
+ what flights go from phoenix to salt lake city
448
+ i need an early flight from milwaukee to denver
449
+ what types of ground transportation are available in denver
450
+ what flights go from denver to st. louis on tuesday morning
451
+ is ground transportation available in st. louis
452
+ i need to fly from st. louis to milwaukee on wednesday afternoon
453
+ flights from washington to seattle
454
+ flights from atlanta to seattle
455
+ flights from san diego to seattle
456
+ i would like flight information from phoenix to denver
457
+ could i have flight information on flights from salt lake city to phoenix please
458
+ could i have flight information on flights from pittsburgh to phoenix please
459
+ i would like information on flights leaving from washington dc to denver
460
+ i need information on flights from washington to boston that leave on a saturday
461
+ i need the flights from washington to montreal on a saturday
462
+ i need the fares on flights from washington to toronto on a saturday
463
+ i want to go from boston to washington on a saturday
464
+ i need a flight from cleveland to dallas that leaves before noon see if too much information
465
+ get fares from washington to boston
466
+ get saturday fares from washington to boston
467
+ get fares from washington to montreal
468
+ get saturday fares from washington to montreal
469
+ get saturday fares from washington to toronto
470
+ get the saturday fare from washington to toronto
471
+ list saturday flights from washington to boston
472
+ list saturday flights from boston to washington
473
+ get flights from milwaukee to dtw
474
+ list flights from milwaukee to detroit
475
+ get flights from detroit to toronto
476
+ get flights from toronto to milwaukee
477
+ get last flight from oakland to salt lake city on wednesday or first flight from oakland to salt lake city on thursday
478
+ get first flight from oakland to salt lake city on thursday
479
+ get last flight from oakland to salt lake city on wednesday
480
+ list last wednesday flight from oakland to salt lake city
481
+ get flight from toronto to san diego stopping at dtw
482
+ get flights between st. petersburg and charlotte
483
+ i need a flight from milwaukee to indianapolis leaving monday before 9 am
484
+ i need a flight departing from milwaukee to indianapolis leaving monday before 8 am
485
+ is there ground transportation available at the indianapolis airport
486
+ i need flight information for a flight departing from indianapolis to cleveland departing tuesday at noon
487
+ i need flight information for a flight departing from cleveland to milwaukee wednesday after 6 pm
488
+ i need flight information for flights departing from cleveland going back to milwaukee wednesday after 5 pm
489
+ i need flight information for flights departing from cleveland to milwaukee on wednesday after 5 pm
490
+ i need flight information for flights departing from cleveland to milwaukee on wednesday after 5 pm
491
+ i need a flight from denver to salt lake city on monday
492
+ is there ground transportation available at the denver airport
493
+ i need flight and airline information for a flight from denver to salt lake city on monday departing after 5 pm
494
+ is there ground transportation available at the salt lake city airport
495
+ i need a flight from salt lake city to phoenix departing wednesday after 5 pm
496
+ is there ground transportation available at the phoenix airport
497
+ i need a flight from oakland to salt lake city on wednesday departing after 6 pm
498
+ i need flight and fare information for thursday departing prior to 9 am from oakland going to salt lake city
499
+ i need flight and fare information departing from oakland to salt lake city on thursday before 8 am
500
+ i need flight numbers and airlines for flights departing from oakland to salt lake city on thursday departing before 8 am
501
+ i need flight numbers for those flights departing on thursday before 8 am from oakland going to salt lake city
502
+ list airports in arizona nevada and california please
503
+ list california nevada arizona airports
504
+ list the arizona airport
505
+ list california airports
506
+ list flights from las vegas to phoenix
507
+ list california airports
508
+ list airports
509
+ list wednesday night flights from oakland to salt lake city
510
+ list flights from oakland to salt lake city before 6 am thursday morning
511
+ which airlines fly between toronto and san diego
512
+ please list afternoon flights between st. petersburg and charlotte
513
+ what is tpa
514
+ what are the flights from cleveland to dallas
515
+ please list only the flights from cleveland to dallas that leave before noon
516
+ what type of aircraft are flying from cleveland to dallas before noon
517
+ i need information on flights from indianapolis to seattle
518
+ i need a flight from memphis to seattle
519
+ i need a ticket from nashville to seattle
520
+ i need a ticket from nashville tennessee to seattle
521
+ i need flight information from milwaukee to tampa
522
+ i need to rent a car at tampa
523
+ i need a daily flight from st. louis to milwaukee
524
+ i need flights departing from oakland and arriving salt lake city
525
+ i need information on flights from toronto to san diego
526
+ i need information on flights from toronto to san diego
527
+ i want a flight from toronto to san diego
528
+ i need information on flights between st. petersburg and charlotte
529
+ i need the flight numbers of flights leaving from cleveland and arriving at dallas
530
+ which flights go from new york to miami and back
531
+ what does fare code qo mean
532
+ show me flights from milwaukee to orlando one way
533
+ what the abbreviation us stand for
534
+ i'd like a one way ticket from milwaukee to orlando either wednesday evening or thursday morning
535
+ show me flights from milwaukee to orlando
536
+ what does fare code f mean
537
+ what does fare code h mean
538
+ what does fare code y mean
539
+ what are restrictions ap 57
540
+ please show me first class flights from indianapolis to memphis one way leaving before 10 am
541
+ now show me all round trip flights from burbank to seattle that arrive before 7 pm in seattle
542
+ round trip flights from orlando to montreal please
543
+ what airline is dl
544
+ show me all delta airlines flights from montreal to orlando
545
+ show me all flights from orlando to montreal please
546
+ which airline is kw
547
+ please list all flights from new york to miami any any type of class
548
+ what does fare code bh mean
549
+ show me a return flight from miami to jfk please
550
+ what does fare code bh mean
551
+ what does fare code bh mean
552
+ what does fare code bh mean
553
+ what does fare code bh mean
554
+ show me one way flights from milwaukee to orlando after 6 pm on wednesday
555
+ show me the flights from indianapolis to memphis
556
+ show me round trip flights from burbank to seattle
557
+ show me round trip flights from orlando to montreal
558
+ show me nonstop flights from montreal to orlando
559
+ show me round trips between montreal and orlando
560
+ show me round trip flights from montreal to orlando
561
+ show me the cheapest one way flights from montreal to orlando
562
+ show me the cheapest one way flights from orlando to montreal
563
+ show me the cheapest economy flights from miami to new york
564
+ kansas city to las vegas economy
565
+ kansas city to las vegas economy
566
+ what airline is hp
567
+ ground transportation in las vegas
568
+ ground transportation for las vegas
569
+ las vegas to baltimore economy
570
+ las vegas to baltimore economy
571
+ baltimore to kansas city economy
572
+ what airline is us
573
+ which airline is us
574
+ which airline is us
575
+ which airline is us
576
+ which airline is us
577
+ columbus to chicago one way before 10 am
578
+ what airline is hp
579
+ st. petersburg to detroit
580
+ from milwaukee to orlando one way after 5 pm wednesday
581
+ and from milwaukee to atlanta before 10 am daily
582
+ what airline is yx
583
+ show me all flights from san jose to phoenix
584
+ show me all flights from san jose to phoenix
585
+ what airline is hp
586
+ show me ground transportation in phoenix
587
+ show me flights from phoenix to fort worth
588
+ show me ground transportation in fort worth
589
+ show me flights from fort worth to san jose
590
+ show me first class flights from new york to miami round trip
591
+ show me first class flights from new york to miami round trip
592
+ show me all round trip flights from new york to miami nonstop
593
+ show me all round trip flights from miami to new york nonstop
594
+ show me one way flights from indianapolis to memphis before 10 am on any day
595
+ what does fare code f mean
596
+ show me round trip flights from burbank to tacoma
597
+ what does the restriction ap58 mean
598
+ what does fare code h mean
599
+ what airline is as
600
+ what airline is as
601
+ what airline is as
602
+ what airline is as as in sam
603
+ show me nonstop flights from st. petersburg to toronto
604
+ show me nonstop flights from toronto to st. petersburg
605
+ show me the nonstop flights and fares from toronto to st. petersburg
606
+ show me the nonstop flights from toronto to st. petersburg
607
+ show me weekday flights from milwaukee to orlando one way
608
+ show me weekday flights from milwaukee to orlando one way
609
+ what airline is hp
610
+ list flights from chicago to san diego
611
+ list flights from chicago to san diego
612
+ list flights from kansas city to denver
613
+ list flights from denver to phoenix
614
+ list flights from phoenix to las vegas
615
+ list flights from las vegas to san diego
616
+ list flights from chicago to kansas city in the morning
617
+ list flights from houston to san jose
618
+ list flights from houston to milwaukee
619
+ list flights from milwaukee to san jose on wednesday
620
+ list flights from san jose to dallas on friday
621
+ list flights from dallas to houston
622
+ list distance from airports to downtown in new york
623
+ list airports in new york
624
+ list airports in new york
625
+ list airports in la
626
+ list airports
627
+ list airports in la
628
+ list airports in la
629
+ list the airports in la
630
+ list la
631
+ list la
632
+ list flights from new york to la
633
+ list flights from la guardia to burbank
634
+ list flights from la to orlando
635
+ list flights from ontario california to orlando
636
+ list flights from ontario california to orlando
637
+ list flights from indianapolis to memphis with fares on monday
638
+ list flights from indianapolis to memphis on monday
639
+ list flights from memphis to miami on wednesday
640
+ list flights from miami to indianapolis on sunday
641
+ list flights from charlotte on saturday afternoon
642
+ list type of aircraft for all flights from charlotte
643
+ list flights and fares from tacoma to orlando round trip leaving saturday returning next saturday
644
+ what class is fare code q
645
+ list flights from orlando to tacoma on saturday of fare basis code of q
646
+ list airfares for first class round trip from detroit to st. petersburg
647
+ list coach round trip airfare from detroit to st. petersburg
648
+ list flights from pittsburgh to newark on monday morning
649
+ list flights from minneapolis to pittsburgh on friday
650
+ list flights before 9 am from cincinnati to tampa
651
+ list flights from cincinnati to tampa before noon
652
+ list flights from tampa to cincinnati after 3 pm
653
+ list airlines that fly from seattle to salt lake city
654
+ list delta flights from seattle to salt lake city
655
+ list seating capacities of delta flights from seattle to salt lake city
656
+ list delta flights from seattle to salt lake city with aircraft type
657
+ what ground transportation is there in baltimore
658
+ list ground transportation in baltimore
659
+ list flights from baltimore to san francisco on friday
660
+ give me the flights from los angeles to pittsburgh on tuesday
661
+ give me the flights from pittsburgh to los angeles thursday evening
662
+ give me the round trip flights from cleveland to miami next wednesday
663
+ give me the fares for round trip flights from cleveland to miami next wednesday
664
+ give me the flights and fares for a trip to cleveland from miami on wednesday
665
+ give me the fares from miami to cleveland next sunday
666
+ give me the flights from milwaukee to phoenix on saturday or sunday on american airlines
667
+ give me the flights from phoenix to milwaukee on wednesday evening
668
+ give me the flights from phoenix to milwaukee on wednesday on american airlines
669
+ give me the flights from phoenix to milwaukee on american airlines
670
+ give me the flights from phoenix to milwaukee
671
+ give me the meal flights departing early saturday morning from chicago to seattle nonstop
672
+ give me the flights from chicago to seattle saturday morning that have meals
673
+ give me flights from seattle to chicago that have meals on continental
674
+ give me the flights from seattle to chicago that have meals on continental saturday morning
675
+ give me the flights from chicago to seattle on continental that have meals early saturday morning
676
+ give me a combination of continental flights from chicago to seattle that have meals early saturday morning
677
+ give me the saturday morning flights with meals from chicago to minneapolis
678
+ give me the saturday morning flights on continental that have meals from chicago to minneapolis
679
+ give me the saturday morning flights from chicago to st. paul on continental that have meals
680
+ give me the flights from new york to las vegas nonstop
681
+ give me the flights from memphis to las vegas nonstop
682
+ give me the cheapest round trip flights from indianapolis to orlando around december twenty fifth
683
+ i need a friday flight from newark to tampa
684
+ i need a sunday flight from tampa to charlotte
685
+ give me a flight from charlotte to baltimore on tuesday morning
686
+ can i have a morning flight from baltimore to newark please
687
+ cheapest round trip fare from or indianapolis to orlando on december twenty fifth
688
+ cheapest one way fare from indianapolis to orlando on december twenty seventh
689
+ flight number from dallas to houston
690
+ flight number from houston to dallas
691
+ saturday flight on american airlines from milwaukee to phoenix
692
+ flight numbers on american airlines from phoenix to milwaukee
693
+ flight numbers from chicago to seattle
694
+ flight numbers from chicago to seattle on continental
695
+ flight numbers from seattle to chicago on continental
696
+ is there a fare from pittsburgh to cleveland under 200 dollars
697
+ how much is coach flight from pittsburgh to atlanta
698
+ newark to tampa on friday
699
+ tampa to charlotte sunday morning
700
+ charlotte to baltimore on tuesday
701
+ baltimore to newark wednesday morning
702
+ dallas to houston after 1201 am
703
+ houston to dallas before midnight
704
+ indianapolis to orlando december twenty seventh
705
+ cheapest fare from indianapolis to orlando on the twenty seventh of december
706
+ cheapest fare round trip from indianapolis to orlando on december twenty seventh
707
+ cleveland to miami on wednesday arriving before 4 pm
708
+ miami to cleveland sunday afternoon
709
+ new york city to las vegas and memphis to las vegas on sunday
710
+ new york city to las vegas and memphis to las vegas on sunday
711
+ new york to las vegas sunday afternoon
712
+ memphis to las vegas sunday afternoon
713
+ new york to las vegas on sunday afternoon
714
+ chicago to seattle saturday morning
715
+ chicago to las vegas saturday morning
716
+ los angeles to pittsburgh afternoon tuesday
717
+ los angeles to pittsburgh afternoon on monday
718
+ pittsburgh to los angeles thursday evening
719
+ milwaukee to phoenix on saturday
720
+ phoenix to milwaukee on sunday
721
+ phoenix to milwaukee on wednesday
722
+ a flight from baltimore to san francisco arriving between 5 and 8 pm
723
+ how many northwest flights leave st. paul
724
+ how many northwest flights leave washington dc
725
+ how many flights does northwest have leaving dulles
726
+ what cities does northwest fly out of
727
+ list the cities from which northwest flies
728
+ what cities does northwest fly to
729
+ i would like a connecting flight from dallas to san francisco leaving after 4 o'clock
730
+ please list all the flights from dallas to san francisco
731
+ tell me again the morning flights on american airlines from philadelphia to dallas
732
+ tell me the flights that leave philadelphia and go to dallas
733
+ what is a d9s
734
+ what type of plane is a d9s
735
+ what is a d9s
736
+ show me the airports serviced by tower air
737
+ show me the first class and coach flights between jfk and orlando
738
+ show me the first class and coach flights from kennedy airport to miami
739
+ show me the first class and coach flights from jfk to miami
740
+ are meals ever served on tower air
741
+ are snacks served on tower air
742
+ show delta airlines flights from jfk to miami
743
+ show delta airlines from boston to salt lake
744
+ show delta airlines flights from boston to salt lake
745
+ show delta airlines flights from boston to salt lake city
746
+ what are the fares for flights between boston and washington dc
747
+ what is the least expensive fare from boston to salt lake city
748
+ what are the lowest fares from washington dc to salt lake city
749
+ what is the lowest fare from bwi to salt lake city
750
+ show me the cost of a first class ticket from detroit to las vegas and back
751
+ what is the earliest arriving flight from boston to washington dc
752
+ what is the earliest arriving flight between boston and washington dc
753
+ what's the earliest arriving flight between boston and washington dc
754
+ what is the earliest arriving flight from houston to orlando
755
+ what is the earliest arriving flight from houston to orlando
756
+ show me the flights between houston and orlando
757
+ show me the flights between houston and orlando
758
+ show me the flights from houston to orlando
759
+ list all flights leaving denver between 8 pm and 9 pm
760
+ what is the seating capacity on the aircraft 733
761
+ what is the seating capacity of a 72s
762
+ what is the seating capacity of the aircraft 72s
763
+ what is the seating capacity of the aircraft m80
764
+ what is the seating capacity of the type of aircraft m80
765
+ what is the seating capacity of an m80
766
+ what airlines serve denver
767
+ list the airlines with flights to or from denver
768
+ what airlines fly into denver
769
+ list all flights arriving in denver between 8 and 9 pm
770
+ what is the capacity of the 73s
771
+ what is 73s
772
+ what is seating capacity on the aircraft 73s
773
+ what is the seating capacity of a 757
774
+ how many people will a 757 hold
775
+ how many passengers can fly on a 757
776
+ list all of the daily flights arriving in denver between 8 and 9 pm
777
+ list all of the daily flights arriving in denver from 8 to 9 pm
778
+ show me all of the daily flights arriving in denver between 8 pm and 9 pm
779
+ what is the seating capacity of the 757
780
+ tell me about the m80 aircraft
781
+ tell me about the m80 aircraft
782
+ tell me about the type of aircraft called an m80
783
+ what is the seating capacity of the 733
784
+ what is the seating capacity of the m80
785
+ what is the seating capacity on the aircraft m80
786
+ list all flights arriving or leaving denver between 8 and 9 pm
787
+ list all flights arriving in denver between 8 and 9 pm
788
+ list all flights on all types of aircraft arriving in denver between 8 and 9 pm
789
+ please list all flights from nashville to memphis on monday morning
790
+ please list the flights from nashville to memphis on monday morning
791
+ is there ground transportation from the memphis airport into town when if i arrive at 842 in the morning
792
+ please list the flights from memphis to new york city on a monday night
793
+ what is cvg
794
+ what ground transportation is available from la guardia airport into new york city
795
+ is there ground transportation from lga into new york city
796
+ please list the ground transportation from lga into new york city
797
+ please list ground transportation from ewr into new york city
798
+ show me the morning flights from memphis to new york city
799
+ give me the flights from new york city to nashville leaving after 5 pm on wednesday
800
+ tell me about the ground transportation from nashville airport
801
+ what are the nonstop flights from cincinnati to charlotte leaving after noon and arriving before 7 pm
802
+ how many flights does alaska airlines have to burbank
803
+ list the alaska airline flights from burbank to anywhere
804
+ list the alaska airline flights from burbank
805
+ which airline is as
806
+ list the alaska airlines flights arriving in burbank
807
+ list the alaska airlines flights a departing from burbank
808
+ list all alaska airlines flights
809
+ list all flights departing from seattle
810
+ list the flights from indianapolis to memphis that leave before noon
811
+ list the cheapest fare from charlotte to las vegas
812
+ i want a flight from los angeles to charlotte early in the morning
813
+ i would like a morning flight from charlotte to newark
814
+ i'd like a morning flight from newark to los angeles
815
+ i'd like an evening flight from newark to los angeles
816
+ i would like a flight that leaves on sunday from montreal quebec to san diego california
817
+ i would like a flight on tuesday which leaves from san diego to indianapolis indiana and that leaves in the afternoon
818
+ i would like to leave thursday morning from indianapolis to toronto
819
+ i would like a flight on friday morning from toronto to montreal
820
+ i would like a flight from cincinnati to burbank on american
821
+ what type of aircraft is used for the american flight leaving at 419 pm
822
+ i need a flight leaving kansas city to chicago leaving next wednesday and returning the following day
823
+ what flights go from long beach to st. louis
824
+ what are the flights from memphis to las vegas
825
+ what are the flights from las vegas to ontario
826
+ what are the flights from ontario to memphis
827
+ what type of ground transportation is there at the las vegas airport
828
+ is there taxi service at the ontario airport
829
+ what are the flights from tampa to milwaukee
830
+ what are the flights from milwaukee to seattle
831
+ what are the flights from la guardia to san jose on united
832
+ what are the flights on mondays that travel from charlotte north carolina to phoenix arizona
833
+ what are the flights from phoenix arizona to st. paul minnesota on tuesday
834
+ what are the flights on thursday leaving from st. paul minnesota to st. louis
835
+ what are the flights from st. louis to charlotte north carolina leaving on friday
836
+ what are the flights from boston to orlando that stop in new york
837
+ i need a morning flight from burbank to milwaukee on next monday
838
+ how about a flight from milwaukee to st. louis that leaves monday night
839
+ and a flight from st. louis to burbank that leaves tuesday afternoon
840
+ how about a flight leaving tuesday night from st. louis to burbank
841
+ i need a flight from salt lake to newark airport that arrives on saturday before 6 pm
842
+ i'd like a flight from cincinnati to newark airport that arrives on saturday before 6 pm
843
+ i need a flight on american airlines from miami to chicago that arrives around 5 pm
844
+ i need a flight from memphis to tacoma that goes through los angeles
845
+ what are the flights between cincinnati and san jose california which leave after 6 pm
846
+ what are the nonstop flights between san jose and houston texas
847
+ what are the nonstop flights between houston and memphis
848
+ what are the flights between memphis and cincinnati on wednesday
849
+ what are the american flights from newark to nashville
850
+ the flights from ontario to westchester that stop in chicago
851
+ please list the flights from los angeles to charlotte
852
+ please list the flights from charlotte to newark
853
+ please list the flights from newark to los angeles
854
+ please list the flights from cincinnati to burbank on american airlines
855
+ please give me the flights from kansas city to chicago on june sixteenth
856
+ please give me the flights from chicago to kansas city on june seventeenth
857
+ please list all the flights from kansas city to chicago on june sixteenth
858
+ please list all the flights from chicago to kansas city on june seventeenth
859
+ i'd like to travel from burbank to milwaukee
860
+ can you find me a flight from salt lake city to new york city next saturday before arriving before 6 pm
861
+ can you find me another flight from cincinnati to new york on saturday before 6 pm
862
+ can you list all of the delta flights from salt lake city to new york next saturday arriving before 6 pm
863
+ i'd like to fly from miami to chicago on on american airlines arriving around 5 pm
864
+ i'd like to travel from kansas city to chicago next wednesday
865
+ i'd like a round trip flight from kansas city to chicago on wednesday may twenty sixth arriving at 7 pm
866
+ yes i'd like to find a flight from memphis to tacoma stopping in los angeles
867
+ find flight from san diego to phoenix on monday am
868
+ find flight from phoenix to detroit on monday
869
+ find flight from detroit to san diego on tuesday
870
+ find flight from cincinnati to san jose on monday
871
+ find flight from san jose to houston on wednesday
872
+ find flight from houston to memphis on friday
873
+ find flight from memphis to cincinnati on sunday
874
+ find american flight from newark to nashville around 630 pm
875
+ please find a flight round trip from los angeles to tacoma washington with a stopover in san francisco not exceeding the price of 300 dollars for june tenth 1993
876
+ are there any flights on june tenth from burbank to tacoma
877
+ please find a flight from ontario to westchester that makes a stop in chicago on may seventeenth one way with dinner
878
+ like to book a flight from burbank to milwaukee
879
+ show me all the flights from burbank to milwaukee
880
+ find me all the flights from milwaukee to st. louis
881
+ now show me all the flights from st. louis to burbank
882
+ is there one airline that flies from burbank to milwaukee milwaukee to st. louis and from st. louis to burbank
883
+ find me all the round trip flights from burbank to milwaukee stopping in st. louis
884
+ i'd like to book two flights to westchester county
885
+ i want to book a flight from salt lake city to westchester county
886
+ tell me all the airports near westchester county
887
+ i'd like to book a flight from cincinnati to new york city on united airlines for next saturday
888
+ tell me all the airports in the new york city area
889
+ please find all the flights from cincinnati to any airport in the new york city area that arrive next saturday before 6 pm
890
+ find me a flight from cincinnati to any airport in the new york city area
891
+ i'd like to fly from miami to chicago on american airlines
892
+ i would like to book a round trip flight from kansas city to chicago
893
+ find me a flight that flies from memphis to tacoma
JointBERT-master/data/atis/test/seq.out ADDED
@@ -0,0 +1,893 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ O O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O O O B-stoploc.city_name I-stoploc.city_name
2
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3
+ O B-depart_date.month_name B-depart_date.day_number O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
4
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5
+ O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number O B-airline_name I-airline_name
6
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7
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8
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9
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10
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_date.month_name B-depart_date.day_number
11
+ O O O O B-fromloc.city_name O B-toloc.city_name B-meal_description
12
+ O B-depart_date.date_relative B-depart_date.day_name O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O O B-toloc.city_name B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time O O O B-return_date.day_name
13
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.date_relative B-depart_date.day_name O O B-toloc.city_name B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
14
+ O O B-airline_name O B-fromloc.city_name O B-toloc.city_name O O B-toloc.city_name B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
15
+ O O O B-toloc.city_name I-toloc.city_name I-toloc.city_name B-arrive_date.date_relative B-arrive_date.day_name
16
+ O B-flight_stop O O B-fromloc.city_name I-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name B-depart_date.month_name B-depart_date.day_number
17
+ O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.today_relative
18
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19
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20
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21
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22
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23
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24
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25
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26
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27
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28
+ O O O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name
29
+ O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
30
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31
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32
+ O O O O B-fromloc.city_name O B-toloc.city_name
33
+ O B-airport_name I-airport_name O O O O O O O O O
34
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35
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36
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37
+ O O O O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O
38
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39
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40
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41
+ O O O O O B-fromloc.city_name O B-toloc.city_name B-connect O B-stoploc.city_name
42
+ O O O O B-meal_description
43
+ O O O O O B-fromloc.city_name O B-toloc.city_name
44
+ O O O B-flight_stop O O B-fromloc.city_name O B-toloc.city_name
45
+ O O O B-flight_stop O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
46
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47
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
48
+ O O O O O B-airline_name I-airline_name O B-fromloc.airport_name I-fromloc.airport_name O B-toloc.city_name I-toloc.city_name
49
+ O O O O O B-fromloc.city_name O B-toloc.city_name
50
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51
+ O B-meal O O O B-airline_name O B-flight_number O B-fromloc.city_name O B-toloc.city_name
52
+ O B-meal O O O B-airline_name O B-flight_number I-flight_number O B-fromloc.city_name O B-toloc.city_name
53
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
54
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55
+ O O O O O B-fromloc.city_name O B-toloc.city_name
56
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57
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58
+ O O O B-fromloc.city_name O O O B-toloc.city_name I-toloc.city_name B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
59
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60
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61
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62
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63
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64
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65
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+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O O O O B-stoploc.city_name O O O O O B-meal_description O O O
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82
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.state_name
83
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84
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85
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-airline_name I-airline_name
86
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87
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88
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89
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90
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91
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92
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93
+ O O O O O O B-fromloc.city_name O B-toloc.city_name O B-stoploc.city_name O O B-depart_time.period_of_day
94
+ O O O O O O O O O B-city_name I-city_name
95
+ O O O O B-toloc.city_name O O O O O O O B-fromloc.city_name I-fromloc.city_name
96
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97
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98
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99
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100
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101
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102
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103
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104
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105
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106
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107
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108
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109
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110
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111
+ O O O B-flight_mod B-meal_description O O B-fromloc.city_name O B-toloc.city_name
112
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113
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114
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115
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116
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117
+ O O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name
118
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119
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120
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121
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122
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123
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124
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125
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126
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127
+ O O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day
128
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129
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130
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
131
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132
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133
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
134
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135
+ O O O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number B-depart_time.time_relative B-depart_time.time I-depart_time.time
136
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-arrive_date.month_name B-arrive_date.day_number B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
137
+ O O O O O B-city_name
138
+ O O O O O B-transport_type O B-city_name
139
+ O O O O O O O O B-city_name
140
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number B-depart_time.time_relative B-depart_time.time I-depart_time.time
141
+ O O O O O B-city_name I-city_name
142
+ O O O O O B-airline_name I-airline_name O O B-depart_date.month_name B-depart_date.day_number O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.time I-depart_time.time
143
+ O B-airline_name I-airline_name O O B-depart_date.month_name B-depart_date.day_number O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
144
+ O B-depart_date.month_name B-depart_date.day_number O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
145
+ O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
146
+ O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
147
+ O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
148
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
149
+ O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
150
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
151
+ O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
152
+ O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number B-depart_time.time_relative B-depart_time.time I-depart_time.time
153
+ O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
154
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number O B-depart_time.time_relative B-depart_time.time I-depart_time.time
155
+ O O O O B-fromloc.airport_name I-fromloc.airport_name O B-depart_time.start_time O B-depart_time.end_time I-depart_time.end_time O B-depart_date.month_name B-depart_date.day_number
156
+ O O O O B-toloc.airport_name I-toloc.airport_name O B-arrive_date.month_name B-arrive_date.day_number
157
+ O O O O B-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.time I-depart_time.time
158
+ O O O O B-fromloc.city_name O B-toloc.city_name
159
+ O O O O B-fromloc.city_name O B-toloc.city_name
160
+ O O O O B-fromloc.city_name O B-toloc.city_name O O B-arrive_date.month_name B-arrive_date.day_number
161
+ O O O O B-fromloc.city_name O B-toloc.city_name O B-arrive_date.month_name B-arrive_date.day_number
162
+ O O O O B-fromloc.city_name O B-toloc.city_name O O B-arrive_date.month_name B-arrive_date.day_number
163
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164
+ O O B-airline_name I-airline_name I-airline_name O O B-aircraft_code
165
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166
+ O O B-airline_name I-airline_name O O O B-aircraft_code
167
+ O O O O O B-airline_name I-airline_name O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-toloc.country_name O O O O B-stoploc.city_name I-stoploc.city_name
168
+ O O O O O B-airline_name I-airline_name O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-toloc.state_name O O O B-stoploc.city_name I-stoploc.city_name
169
+ O O O B-mod O B-city_name B-state_name
170
+ O O O O O B-fromloc.city_name O B-toloc.city_name
171
+ O O O O O B-fromloc.city_name O B-toloc.city_name
172
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
173
+ O O O B-cost_relative B-round_trip I-round_trip B-class_type O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
174
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175
+ O O O B-airline_name O O O O B-meal_description O B-compartment O
176
+ O O O O B-meal_code
177
+ O B-meal O O O B-airline_code B-flight_number O O O O B-toloc.city_name I-toloc.city_name O B-arrive_time.time I-arrive_time.time
178
+ O O O B-airline_name O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
179
+ O O B-airline_name O B-flight_number
180
+ O O B-airline_name I-airline_name O O B-day_name
181
+ O O B-airline_name I-airline_name O O B-meal
182
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183
+ O O O O B-fromloc.city_name O O O B-toloc.city_name I-toloc.city_name O O B-arrive_date.day_name
184
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185
+ O O O O B-fromloc.city_name O O O B-toloc.city_name O O B-arrive_time.period_of_day
186
+ O O O O B-fromloc.city_name O O B-depart_time.period_of_day B-depart_time.period_of_day O O O B-toloc.city_name
187
+ O O O O B-fromloc.city_name O O O B-toloc.city_name
188
+ O O O O O B-fromloc.city_name O O O B-toloc.city_name
189
+ O O O O B-fromloc.city_name O O O B-toloc.city_name B-toloc.state_code
190
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191
+ O O O B-city_name I-city_name B-airport_name I-airport_name O O
192
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193
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194
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195
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196
+ O O O O B-transport_type O O B-airport_name I-airport_name
197
+ O O O O B-transport_type O O B-airport_name I-airport_name
198
+ O O O B-transport_type O O B-city_name I-city_name
199
+ O O O O B-fromloc.city_name B-fromloc.state_code O B-toloc.city_name B-toloc.state_name
200
+ O O O O O B-fromloc.city_name B-fromloc.state_code O B-toloc.city_name B-toloc.state_name
201
+ O O O O O B-fromloc.city_name B-fromloc.state_code O B-toloc.city_name B-toloc.state_name
202
+ O O O O O O O O B-fromloc.city_name O B-toloc.city_name
203
+ O O B-city_name I-city_name O O O O O O O O O B-airline_name I-airline_name
204
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205
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206
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207
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208
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209
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210
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211
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212
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213
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214
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215
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216
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217
+ O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O
218
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-depart_time.period_mod B-depart_date.day_name B-depart_time.period_of_day
219
+ O O O O B-fromloc.city_name O O O B-toloc.city_name I-toloc.city_name B-arrive_time.time_relative O B-arrive_time.time I-arrive_time.time O B-arrive_date.day_name
220
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O B-depart_time.time_relative B-depart_time.time I-depart_time.time B-depart_date.day_name B-depart_time.period_of_day
221
+ O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-depart_date.day_name O O B-depart_time.period_of_day O O B-meal O
222
+ O B-depart_time.period_of_day B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
223
+ O B-depart_time.period_of_day B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
224
+ O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
225
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226
+ O O O B-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
227
+ O O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code B-depart_date.day_name B-depart_time.period_of_day
228
+ O O O B-fromloc.city_name B-fromloc.state_code O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
229
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230
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231
+ O O O O B-fare_basis_code
232
+ O O O O O O B-fromloc.airport_name I-fromloc.airport_name O O B-city_name
233
+ O O O O O O B-fromloc.city_name I-fromloc.city_name B-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name O O B-city_name I-city_name I-city_name
234
+ O O O O O O B-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name O O B-city_name
235
+ O O O O O O B-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name I-fromloc.airport_name O B-toloc.city_name I-toloc.city_name O
236
+ O B-transport_type O O O B-city_name I-city_name I-city_name
237
+ O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day
238
+ O O O B-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
239
+ O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-depart_date.day_name
240
+ O B-airline_name I-airline_name O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
241
+ O O O B-fromloc.city_name O B-toloc.city_name O B-arrive_date.day_name B-arrive_time.period_of_day
242
+ O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
243
+ O O O O O O O B-aircraft_code
244
+ O O O O O O B-airline_name B-aircraft_code
245
+ O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name O B-airline_name B-aircraft_code
246
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247
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248
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249
+ O O O B-fromloc.city_name O B-toloc.city_name B-flight_days
250
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251
+ O B-airline_name I-airline_name O O B-depart_date.day_name O B-fromloc.airport_name I-fromloc.airport_name B-depart_time.time_relative B-depart_time.time I-depart_time.time
252
+ O B-class_type I-class_type O B-round_trip I-round_trip O B-fromloc.city_name O B-toloc.city_name
253
+ O O O O B-fare_basis_code
254
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255
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256
+ O O O B-fromloc.city_name B-fromloc.state_name O B-toloc.city_name B-toloc.state_name
257
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258
+ O O O B-fromloc.city_name B-fromloc.state_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name B-toloc.state_name B-depart_date.day_name
259
+ O O O B-fromloc.city_name I-fromloc.city_name I-fromloc.city_name B-fromloc.state_name O B-toloc.city_name B-toloc.state_name B-depart_date.day_name
260
+ O O O B-fromloc.city_name I-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-toloc.state_name B-depart_date.day_name
261
+ O O O B-fromloc.city_name B-fromloc.state_name O B-toloc.city_name B-toloc.state_name B-depart_date.day_name
262
+ O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
263
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264
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269
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302
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305
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314
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315
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316
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318
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319
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323
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324
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325
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326
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339
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386
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532
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536
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541
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542
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546
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550
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555
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558
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559
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560
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561
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562
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563
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564
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565
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566
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567
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568
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569
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571
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572
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573
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574
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576
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577
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578
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581
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582
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584
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592
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593
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597
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598
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600
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601
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604
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605
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607
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609
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619
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620
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621
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635
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644
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645
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648
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650
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651
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652
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653
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654
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655
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656
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658
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659
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660
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661
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662
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663
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664
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665
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666
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667
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668
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669
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670
+ O O O O O B-fromloc.city_name O B-toloc.city_name
671
+ O O O B-meal O O B-depart_time.period_mod B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name B-flight_stop
672
+ O O O O O B-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day O O B-meal
673
+ O O O O B-fromloc.city_name O B-toloc.city_name O O B-meal O B-airline_name
674
+ O O O O O B-fromloc.city_name O B-toloc.city_name O O B-meal O B-airline_name B-depart_date.day_name B-depart_time.period_of_day
675
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-airline_name O O B-meal B-depart_time.period_mod B-depart_date.day_name B-depart_time.period_of_day
676
+ O O O O O B-airline_name O O B-fromloc.city_name O B-toloc.city_name O O B-meal B-depart_time.period_mod B-depart_date.day_name B-depart_time.period_of_day
677
+ O O O B-depart_date.day_name B-depart_time.period_of_day O O B-meal O B-fromloc.city_name O B-toloc.city_name
678
+ O O O B-depart_date.day_name B-depart_time.period_of_day O O B-airline_name O O B-meal O B-fromloc.city_name O B-toloc.city_name
679
+ O O O B-depart_date.day_name B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-airline_name O O B-meal
680
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-flight_stop
681
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-flight_stop
682
+ O O O B-cost_relative B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number
683
+ O O O B-depart_date.day_name O O B-fromloc.city_name O B-toloc.city_name
684
+ O O O B-depart_date.day_name O O B-fromloc.city_name O B-toloc.city_name
685
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day
686
+ O O O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name O
687
+ B-cost_relative B-round_trip I-round_trip O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number
688
+ B-cost_relative B-round_trip I-round_trip O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number
689
+ O O O B-fromloc.city_name O B-toloc.city_name
690
+ O O O B-fromloc.city_name O B-toloc.city_name
691
+ B-depart_date.day_name O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name
692
+ O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name
693
+ O O O B-fromloc.city_name O B-toloc.city_name
694
+ O O O B-fromloc.city_name O B-toloc.city_name O B-airline_name
695
+ O O O B-fromloc.city_name O B-toloc.city_name O B-airline_name
696
+ O O O O O B-fromloc.city_name O B-toloc.city_name B-cost_relative B-fare_amount I-fare_amount
697
+ O O O B-class_type O O B-fromloc.city_name O B-toloc.city_name
698
+ B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
699
+ B-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
700
+ B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
701
+ B-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
702
+ B-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.time I-depart_time.time
703
+ B-fromloc.city_name O B-toloc.city_name B-depart_time.time_relative B-depart_time.period_of_day
704
+ B-fromloc.city_name O B-toloc.city_name B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number
705
+ B-cost_relative O O B-fromloc.city_name O B-toloc.city_name O O B-depart_date.day_number I-depart_date.day_number O B-depart_date.month_name
706
+ B-cost_relative O B-round_trip I-round_trip O B-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number I-depart_date.day_number
707
+ B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name O B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
708
+ B-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
709
+ B-fromloc.city_name I-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name
710
+ B-fromloc.city_name I-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name
711
+ B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
712
+ B-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
713
+ B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day
714
+ B-fromloc.city_name O B-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
715
+ B-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
716
+ B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-depart_time.period_of_day B-depart_date.day_name
717
+ B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-depart_time.period_of_day O B-depart_date.day_name
718
+ B-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-depart_date.day_name B-depart_time.period_of_day
719
+ B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
720
+ B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
721
+ B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
722
+ O B-flight O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O B-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
723
+ O O B-airline_name O O B-fromloc.city_name I-fromloc.city_name
724
+ O O B-airline_name O O B-fromloc.city_name B-fromloc.state_code
725
+ O O O O B-airline_name O O B-fromloc.airport_name
726
+ O O O B-airline_name O O O
727
+ O O O O O B-airline_name O
728
+ O O O B-airline_name O O
729
+ O O O O B-connect O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_time.time_relative B-depart_time.time I-depart_time.time
730
+ O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
731
+ O O O O B-depart_time.period_of_day O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name
732
+ O O O O O O B-fromloc.city_name O O O B-toloc.city_name
733
+ O O O B-aircraft_code
734
+ O O O O O O B-aircraft_code
735
+ O O O B-aircraft_code
736
+ O O O O O O B-airline_name I-airline_name
737
+ O O O B-class_type I-class_type O B-class_type O O B-fromloc.airport_code O B-toloc.city_name
738
+ O O O B-class_type I-class_type O B-class_type O O B-fromloc.airport_name I-fromloc.airport_name O B-toloc.city_name
739
+ O O O B-class_type I-class_type O B-class_type O O B-fromloc.airport_code O B-toloc.city_name
740
+ O B-meal O O O B-airline_name I-airline_name
741
+ O B-meal_description O O B-airline_name I-airline_name
742
+ O B-airline_name I-airline_name O O B-fromloc.airport_code O B-toloc.city_name
743
+ O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
744
+ O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
745
+ O B-airline_name I-airline_name O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
746
+ O O O O O O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code
747
+ O O O B-cost_relative I-cost_relative O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
748
+ O O O B-cost_relative O O B-fromloc.city_name B-fromloc.state_code O B-toloc.city_name I-toloc.city_name I-toloc.city_name
749
+ O O O B-cost_relative O O B-fromloc.airport_code O B-toloc.city_name I-toloc.city_name I-toloc.city_name
750
+ O O O O O O B-class_type I-class_type O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-round_trip
751
+ O O O B-flight_mod I-flight_mod O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code
752
+ O O O B-flight_mod I-flight_mod O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code
753
+ O O B-flight_mod I-flight_mod O O B-fromloc.city_name O B-toloc.city_name B-toloc.state_code
754
+ O O O B-flight_mod I-flight_mod O O B-fromloc.city_name O B-toloc.city_name
755
+ O O O B-flight_mod I-flight_mod O O B-fromloc.city_name O B-toloc.city_name
756
+ O O O O O B-fromloc.city_name O B-toloc.city_name
757
+ O O O O O B-fromloc.city_name O B-toloc.city_name
758
+ O O O O O B-fromloc.city_name O B-toloc.city_name
759
+ O O O O B-fromloc.city_name O B-depart_time.start_time I-depart_time.start_time O B-depart_time.end_time I-depart_time.end_time
760
+ O O O O O O O O B-aircraft_code
761
+ O O O O O O O B-aircraft_code
762
+ O O O O O O O O B-aircraft_code
763
+ O O O O O O O O B-aircraft_code
764
+ O O O O O O O O O O B-aircraft_code
765
+ O O O O O O O B-aircraft_code
766
+ O O O B-city_name
767
+ O O O O O O O O B-city_name
768
+ O O O O B-toloc.city_name
769
+ O O O O O B-toloc.city_name O B-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
770
+ O O O O O O B-aircraft_code
771
+ O O B-aircraft_code
772
+ O O O O O O O B-aircraft_code
773
+ O O O O O O O B-aircraft_code
774
+ O O O O O B-aircraft_code O
775
+ O O O O O O O B-aircraft_code
776
+ O O O O B-flight_days O O O B-toloc.city_name O B-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
777
+ O O O O B-flight_days O O O B-toloc.city_name O B-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
778
+ O O O O O B-flight_days O O O B-toloc.city_name O B-arrive_time.start_time I-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
779
+ O O O O O O O B-aircraft_code
780
+ O O O O B-aircraft_code O
781
+ O O O O B-aircraft_code O
782
+ O O O O O O O O O B-aircraft_code
783
+ O O O O O O O B-aircraft_code
784
+ O O O O O O O B-aircraft_code
785
+ O O O O O O O O B-aircraft_code
786
+ O O O O O O B-city_name O B-depart_time.start_time O B-depart_time.end_time I-depart_time.end_time
787
+ O O O O O B-toloc.city_name O B-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
788
+ O O O O O O O O O O B-toloc.city_name O B-arrive_time.start_time O B-arrive_time.end_time I-arrive_time.end_time
789
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day
790
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name B-depart_time.period_of_day
791
+ O O O O O O B-airport_name I-airport_name O O O O O O O O O O B-period_of_day
792
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name O O B-depart_date.day_name B-depart_time.period_of_day
793
+ O O B-airport_code
794
+ O O O O O O B-airport_name I-airport_name I-airport_name O B-city_name I-city_name I-city_name
795
+ O O O O O B-airport_code O B-city_name I-city_name I-city_name
796
+ O O O O O O B-airport_code O B-city_name I-city_name I-city_name
797
+ O O O O O B-airport_code O B-city_name I-city_name I-city_name
798
+ O O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name
799
+ O O O O O B-fromloc.city_name I-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_time.time_relative B-depart_time.time I-depart_time.time O B-depart_date.day_name
800
+ O O O O O O O B-airport_name I-airport_name
801
+ O O O B-flight_stop O O B-fromloc.city_name O B-toloc.city_name O B-depart_time.time_relative B-depart_time.period_of_day O O B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
802
+ O O O O B-airline_name I-airline_name O O B-toloc.city_name
803
+ O O B-airline_name I-airline_name O O B-fromloc.city_name O O
804
+ O O B-airline_name I-airline_name O O B-fromloc.city_name
805
+ O O O B-airline_code
806
+ O O B-airline_name I-airline_name O O O B-toloc.city_name
807
+ O O B-airline_name I-airline_name O O O O B-fromloc.city_name
808
+ O O B-airline_name I-airline_name O
809
+ O O O O O B-fromloc.city_name
810
+ O O O O B-fromloc.city_name O B-toloc.city_name O O B-depart_time.time_relative B-depart_time.period_of_day
811
+ O O B-cost_relative O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
812
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-depart_time.period_mod O O B-depart_time.period_of_day
813
+ O O O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name
814
+ O O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
815
+ O O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
816
+ O O O O O O O O B-depart_date.day_name O B-fromloc.city_name B-fromloc.state_name O B-toloc.city_name I-toloc.city_name B-toloc.state_name
817
+ O O O O O O B-depart_date.day_name O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-toloc.state_name O O O O O B-depart_time.period_of_day
818
+ O O O O O B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name
819
+ O O O O O O B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name O B-toloc.city_name
820
+ O O O O O O B-fromloc.city_name O B-toloc.city_name O B-airline_name
821
+ O O O O O O O O B-airline_name O O O B-depart_time.time I-depart_time.time
822
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.date_relative B-depart_date.day_name O O B-return_date.date_relative I-return_date.date_relative I-return_date.date_relative
823
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name I-toloc.city_name
824
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
825
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
826
+ O O O O O B-fromloc.city_name O B-toloc.city_name
827
+ O O O O O O O O O B-airport_name I-airport_name I-airport_name
828
+ O O B-transport_type I-transport_type O O B-airport_name I-airport_name
829
+ O O O O O B-fromloc.city_name O B-toloc.city_name
830
+ O O O O O B-fromloc.city_name O B-toloc.city_name
831
+ O O O O O B-fromloc.airport_name I-fromloc.airport_name O B-toloc.city_name I-toloc.city_name O B-airline_name
832
+ O O O O O B-depart_date.day_name O O O B-fromloc.city_name B-fromloc.state_name I-fromloc.state_name O B-toloc.city_name B-toloc.state_name
833
+ O O O O O B-fromloc.city_name B-fromloc.state_name O B-toloc.city_name I-toloc.city_name B-toloc.state_name O B-depart_date.day_name
834
+ O O O O O B-depart_date.day_name O O B-fromloc.city_name I-fromloc.city_name B-fromloc.state_name O B-toloc.city_name I-toloc.city_name
835
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-toloc.state_name I-toloc.state_name O O B-depart_date.day_name
836
+ O O O O O B-fromloc.city_name O B-toloc.city_name O O O B-stoploc.city_name I-stoploc.city_name
837
+ O O O B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.date_relative B-depart_date.day_name
838
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O B-depart_date.day_name B-depart_time.period_of_day
839
+ O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O O B-depart_date.day_name B-depart_time.period_of_day
840
+ O O O O O B-depart_date.day_name B-depart_time.period_of_day O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
841
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.airport_name I-toloc.airport_name O O O B-arrive_date.day_name B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
842
+ O O O O O B-fromloc.city_name O B-toloc.airport_name I-toloc.airport_name O O O B-arrive_date.day_name B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
843
+ O O O O O B-airline_name I-airline_name O B-fromloc.city_name O B-toloc.city_name O O B-arrive_time.time_relative B-arrive_time.time I-arrive_time.time
844
+ O O O O O B-fromloc.city_name O B-toloc.city_name O O O B-stoploc.city_name I-stoploc.city_name
845
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name B-toloc.state_name O O B-depart_time.time_relative B-depart_time.time I-depart_time.time
846
+ O O O B-flight_stop O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name B-toloc.state_name
847
+ O O O B-flight_stop O O B-fromloc.city_name O B-toloc.city_name
848
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-depart_date.day_name
849
+ O O O B-airline_name O O B-fromloc.city_name O B-toloc.city_name
850
+ O O O B-fromloc.city_name O B-toloc.city_name O O O B-stoploc.city_name
851
+ O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name
852
+ O O O O O B-fromloc.city_name O B-toloc.city_name
853
+ O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name
854
+ O O O O O B-fromloc.city_name O B-toloc.city_name O B-airline_name I-airline_name
855
+ O O O O O O B-fromloc.city_name I-fromloc.city_name O B-toloc.city_name O B-depart_date.month_name B-depart_date.day_number
856
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3822
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3823
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3824
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3825
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3826
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3827
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3828
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3829
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3830
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3831
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3832
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3833
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3834
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3835
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3836
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3837
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3838
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3839
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3840
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3841
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3842
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3843
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3844
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3845
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3846
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3847
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3848
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3849
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3850
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3851
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3852
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3853
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3854
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3855
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3856
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3857
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3858
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3859
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3860
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3861
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3862
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3863
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3864
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3865
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3866
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3867
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3868
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3869
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3870
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3871
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3872
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3873
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3874
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3875
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3876
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3877
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3878
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3879
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3880
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3881
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3882
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3883
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3884
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3885
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3886
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3887
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3888
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3889
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3890
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3891
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3892
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3893
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3894
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3895
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3896
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3897
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3898
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3899
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3900
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3901
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3902
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3903
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3904
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3905
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3906
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3907
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3908
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3909
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3910
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3911
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3912
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3913
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3914
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3915
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3916
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3917
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3918
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3919
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3920
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3921
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3922
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3923
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3924
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3925
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3926
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3927
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3928
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3929
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3930
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3931
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3932
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3933
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3934
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3935
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3936
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3937
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3938
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3939
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3940
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3941
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3942
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3943
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3944
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3945
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3946
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3947
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3948
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3949
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3950
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3951
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3952
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3953
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3954
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3955
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3956
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3957
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3958
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3959
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3960
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3961
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3962
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3963
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3964
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3965
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3966
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3967
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3968
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3969
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3970
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3971
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3972
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3973
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3974
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3975
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3976
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3977
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3978
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3979
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3980
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3981
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3982
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3983
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3984
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3985
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3986
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3987
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3988
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3989
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3990
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3991
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3992
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3993
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3994
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3995
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3996
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3997
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3998
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3999
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4000
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4001
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4002
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4003
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4004
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4005
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4006
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4007
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4008
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4009
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4010
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4011
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4012
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4013
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4014
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4015
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4016
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4017
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4018
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4019
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4020
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4021
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4022
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4023
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4024
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4025
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4026
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4027
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4028
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4029
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4030
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4031
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4032
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4033
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4034
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4035
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4036
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4037
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4038
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4039
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4040
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4041
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4042
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4043
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4044
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4045
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4046
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4047
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4048
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4049
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4050
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4051
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4052
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4053
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4054
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4055
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4056
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4057
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4058
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4059
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4060
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4061
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4062
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4063
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4064
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4065
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4066
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4067
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4068
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4069
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4070
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4071
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4072
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4073
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4074
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4075
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4076
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4077
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4078
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4079
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4080
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4081
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4082
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4083
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4084
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4085
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4086
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4087
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4088
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4089
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4090
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4091
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4092
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4093
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4094
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4095
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4096
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4097
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4098
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4099
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4100
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4101
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4102
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4103
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4104
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4105
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4106
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4107
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4108
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4109
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4110
+ atis_flight
4111
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4112
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4113
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4114
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4115
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4116
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4117
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4118
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4119
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4120
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4121
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4122
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4123
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4124
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4125
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4126
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4127
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4128
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4129
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4130
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4131
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4132
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4133
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4134
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4135
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4136
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4137
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4138
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4139
+ atis_ground_service
4140
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4141
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4142
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4143
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4144
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4145
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4146
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4147
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4148
+ atis_flight
4149
+ atis_flight
4150
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4151
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4152
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4153
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4154
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4155
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4156
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4157
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4158
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4159
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4160
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4161
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4162
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4163
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4164
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4165
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4166
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4167
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4168
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4169
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4170
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4171
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4172
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4173
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4174
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4175
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4176
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4177
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4178
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4179
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4180
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4181
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4182
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4183
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4184
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4185
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4186
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4187
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4188
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4189
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4190
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4191
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4192
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4193
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4194
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4195
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4196
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4197
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4198
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4199
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4200
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4201
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4202
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4203
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4204
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4205
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4206
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4207
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4208
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4209
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4210
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4211
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4212
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4213
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4214
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4215
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4216
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4217
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4218
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4219
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4220
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4221
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4222
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4223
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4224
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4225
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4226
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4227
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4228
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4229
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4230
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4231
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4232
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4233
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4234
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4235
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4236
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4237
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4238
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4239
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4240
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4241
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4242
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4243
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4244
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4245
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4246
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4247
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4248
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4249
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4250
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4251
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4252
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4253
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4254
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4255
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4256
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4257
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4258
+ atis_flight
4259
+ atis_flight
4260
+ atis_flight
4261
+ atis_flight#atis_airfare
4262
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4263
+ atis_airfare
4264
+ atis_flight
4265
+ atis_flight
4266
+ atis_flight
4267
+ atis_flight
4268
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4269
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4270
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4271
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4272
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4273
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4274
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4275
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4276
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4277
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4278
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4279
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4280
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4281
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4282
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4283
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4284
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4285
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4286
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4287
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4288
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4289
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4290
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4291
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4292
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4293
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4294
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4295
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4296
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4297
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4298
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4299
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4300
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4301
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4302
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4303
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4304
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4305
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4306
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4307
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4308
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4309
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4310
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4311
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4312
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4313
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4314
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4315
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4316
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4317
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4318
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4319
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4320
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4321
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4322
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4323
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4324
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4325
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4326
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4327
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4328
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4329
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4330
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4331
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4332
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4333
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4334
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4335
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4336
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4337
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4338
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4339
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4340
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4341
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4342
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4343
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4344
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4345
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4346
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4347
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4348
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4349
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4350
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4351
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4352
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4353
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4354
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4355
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4356
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4357
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4358
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4359
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4360
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4361
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4362
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4363
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4364
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4365
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4366
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4367
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4368
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4369
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4370
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4371
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4372
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4373
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4374
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4375
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4376
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4377
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4378
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4379
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4380
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4381
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4382
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4383
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4384
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4385
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4386
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4387
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4388
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4389
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4390
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4391
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4392
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4393
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4394
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4395
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4396
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4397
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4398
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4399
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4400
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4401
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4402
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4403
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4404
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4405
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4406
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4407
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4408
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4409
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4410
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4411
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4412
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4413
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4414
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4415
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4416
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4417
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4418
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4419
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4420
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4421
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4422
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4423
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4424
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4425
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4426
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4427
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4428
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4429
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4430
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4431
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4432
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4433
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4434
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4435
+ atis_ground_service
4436
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4437
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4438
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4439
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4440
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4441
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4442
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4443
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4444
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4445
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4446
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4447
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4448
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4449
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4450
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4451
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4452
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4453
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4454
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4455
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4456
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4457
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4458
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4459
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4460
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4461
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4462
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4463
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4464
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4465
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4466
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4467
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4468
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4469
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4470
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4471
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4472
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4473
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4474
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4475
+ atis_flight
4476
+ atis_ground_service
4477
+ atis_flight
4478
+ atis_flight
JointBERT-master/data/atis/train/seq.in ADDED
The diff for this file is too large to render. See raw diff
 
JointBERT-master/data/atis/train/seq.out ADDED
The diff for this file is too large to render. See raw diff
 
JointBERT-master/data/snips/dev/label ADDED
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1
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+ put jean philippe goncalves onto my running to rock 170 to 190 bpm
15
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16
+ onto jerry s classical moments in movies please add the album
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+ add the artist mike to the sexy as folk playlist
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+ add brazilian flag anthem to top 100 alternative tracks on spotify
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+ add andy hunter to my evening commute playlist
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+ put vandemataram srinivas s track onto hiphop hot 50
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+ i d like for you to add bobby brown to my enamorándose playlist
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+ add ireland in the junior eurovision song contest 2015 to my jazzy dinner playlist
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+ add the album to the the sweet suite playlist
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+ add sarah slean to my playlist mellowed out gaming
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+ add this album to the spanish beat playlist
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+ can you put this song from yutaka ozaki onto my this is miles davis playlist
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+ add the famous flower of serving-men to my evening acoustic playlist
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+ i need to add to my infinite indie folk list the works of rahim shah
85
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88
+ a very cellular song needs to be added to my masters of metal playlist
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+ add the album to my club hits playlist
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+ book a reservation for my babies and i
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+ need a table somewhere in quarryville 14 hours from now
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+ what will the weather be faraway from here
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+ will there be fog in tahquamenon falls state park
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+ tell me the weather forecast for gibsland
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+ what will the weather be in monument of lihula on december the 5th
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+ will it be warmer in north korea at nineteen o clock
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+ let me know the weather forecast around ten pm faraway from here in park narodowy brimstone hill fortress
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+ will it be stormy in the ouachita national forest
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+ tell me if it will be snowy 8 hours from now in mount airy vi
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+ what will the weather be nineteen hours from now neighboring saint kitts and nevis
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+ will there be hail on 11/12/2036 in singapore
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+ will it be colder here in 48 and a half weeks
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+ what s the weather going to be in knobel
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+ what will the weather be in dane on sep the fifth 2030
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+ what will the weather be in ohio
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+ i need to know the weather for jan the 3rd in mexico when i go to port vue
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+ what is the forecast for ōtone prefectural natural park in 1 hour and within the same area
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+ what kind of weather is forecast around one pm near vatican
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+ will it be chilly in weldona
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+ will it be colder in virgin islands national park
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+ will it be hot at 13:19 in de funiak springs serbia and montenegro
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+ what is the weather going to be like in virginia on st patrick s day
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+ weather in kaneville maryland
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+ when is sunrise for ar
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+ what will the weather be not far from here on october the nineteenth 2026
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+ what is the forecast for waurika in samoa
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+ tell me the weather forecast here
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+ what is the weather forecast nearby nicodemus
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+ what will the weather be in nov in brookneal
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+ will it be colder four months from now in suwanee ak
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+ what is the weather forecast for burundi
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+ what s the weather in benton city
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+ what will the weather be in ky on oct 16 2036
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+ will the sun be out in 1 minute in searcy uganda
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+ what is the weather here
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+ what will the weather be one second from now in chad
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+ what kind of weather is forecast in ms now
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+ what is the forecast for la for freezing
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+ how cold will it be here in 1 second
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+ what is the forecast for hotter weather at southford falls state park
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+ what is the overcast forecast for the current position starting on jul 19 2030
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+ what is the forecast for morocco at lake ozark on december seventeenth 2022
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+ what will the humidity be in the current spot at 15:19:29
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+ what is the forecast in nicodemus and nearby
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+ what is the weather going to be like in benton colorado in 2 and a half months
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+ what s the weather forecast for bothe-napa valley state park close by february 20
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+ what is the forecast for beginning on nov 17 for franklinville
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+ what s the forecast for sep 26 in emerado saint pierre and miquelon
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+ will there be a blizzard next winter in visalia idaho
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+ will it be warmer in the district of columbia on may 25 2033
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+ what will the weather be here on dec 7th
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+ what is the forecast for colder temps beginning on law day here
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+ what s the weather like in tyonek new jersey
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+ what is the forecast for here for blizzard conditions at five pm
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+ will there be a storm in gibsonia at 8 p m
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+ what is the cold condition of our current position for tomorrow
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+ what will the weather be in hialeah gardens on october the 24th
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+ will it be freezing today in delaware and lehigh national heritage corridor
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+ what is the forecast in admire in tx starting at seventeen
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+ what is the forecast in north carolina for edgemoor
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+ what is the forecast for costa rica
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+ need weather for parc national tolhuaca to see if it will be fog today
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+ weather in walden russia on 12/26/2018
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+ what s the humidity here right now
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+ how s the weather at petit manan national wildlife refuge and nearby right now
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+ what is the forecast for lansford for temperate weather
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+ overcast on state holiday in pawling nature reserve and neighboring places
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+ i need the weather in wakarusa
281
+ tell me the forecast for 6 am in tatra-nationalpark
282
+ tell me the weather forecast for ut on thursday
283
+ what is the forecast for turtle islands national park
284
+ will it be hotter in pr at 23 o clock
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+ weather in two hours in uzbekistan
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+ what is the forecast for this afternoon for blizzard conditions in dieterich chad
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+ how s the weather here at two am
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+ will custer national forest be chillier at seven pm
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+ what is the forecast for starting at three a m in two buttes for warm weather
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+ what is the rain forecast for one hour from now in south korea
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+ tell me the weather forecast here
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+ will there be a cloud in vi in 14 minutes
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+ how much colder will it be not far from utah around 3 am
295
+ will it be chilly midday in cresbard afghanistan
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+ what will the weather be in sarygamyş sanctuary on august 21 2035
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+ will it be rainy in tenino
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+ will it be hot in the netherlands on february 16th
299
+ where is belgium located
300
+ what will the weather be in milleville beach
301
+ can you put on like a hurricane by paul landers
302
+ play the happy blues by ronnie wood
303
+ play the newest melody on last fm by eddie vinson
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+ use groove shark to play music
305
+ please play something good from u-roy any song from 1975 on zvooq will do
306
+ play a symphony from 2013
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+ let me hear the good songs from james iha
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+ play my inventive playlist
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+ i want to play music from iheart
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+ play subconscious lobotomy from jennifer paull
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+ i want to hear a seventies sound track
312
+ play a john maher track
313
+ please play something from dihan slabbert that s on the top fifty
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+ please play something catchy on youtube
315
+ play something from 2004 by imogen heap on spotify
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+ play seventies music please
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+ play music from the artist sean yseult and sort it through top-50
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+ play anything jd natasha did in the thirties
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+ play music off netflix
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+ nineties songs on zvooq
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+ open itunes and play ben burnley ready to die
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+ play an ep by zak starkey
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+ play an album from nithyasree mahadevan
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+ i want to listen to something on youtube
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+ play trance life on zvooq
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+ find and play a concerto on zvooq from 1978 by ginger pooley
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+ play all things must pass
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+ i want to hear music from allen toussaint from the fifties
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331
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+ i want to listen to an ep from 1998
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+ play a fifties album from dj yoda on last fm
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+ let s play jamie robertson s handover on vimeo
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349
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355
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356
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358
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359
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361
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363
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366
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367
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372
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373
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374
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375
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377
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379
+ use the last fm service to play a mis niños de 30
380
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381
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382
+ i want to hear anything from the rock symphonique genre please
383
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384
+ put what color is your sky by alana davis on the stereo
385
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386
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388
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389
+ i want to hear soundtrack music on youtube from helena iren michaelsen
390
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392
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395
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396
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397
+ please play a sound track from the fifties that s on iheart
398
+ play music from van-pires by dmitry malikov
399
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401
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413
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116
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117
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118
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119
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120
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121
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122
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123
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124
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125
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126
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127
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128
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129
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130
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131
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132
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133
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134
+ O O O O O O B-restaurant_type O B-city O O O O B-party_size_number
135
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136
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137
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138
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139
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140
+ O O O O O B-restaurant_type O B-party_size_description I-party_size_description I-party_size_description I-party_size_description I-party_size_description I-party_size_description O B-city B-timeRange I-timeRange I-timeRange I-timeRange
141
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142
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143
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144
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145
+ O O O O O B-restaurant_type O B-city B-timeRange I-timeRange I-timeRange I-timeRange O B-party_size_number O
146
+ O B-party_size_number O B-spatial_relation B-city
147
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148
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149
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150
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151
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152
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153
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154
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155
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156
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157
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158
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159
+ O O O O B-party_size_number O O B-restaurant_type O B-state
160
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161
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162
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163
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164
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165
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166
+ O O O O O O O O B-restaurant_type O B-country I-country
167
+ O O O O O O B-restaurant_type O B-cuisine O O O O O B-state
168
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169
+ O O O O B-party_size_description I-party_size_description I-party_size_description I-party_size_description O O B-cuisine B-restaurant_type O B-timeRange I-timeRange O B-state
170
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171
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172
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173
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174
+ O O O O B-party_size_number O O B-restaurant_type O B-state
175
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176
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177
+ O O O O O B-restaurant_type O B-party_size_number O
178
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179
+ O O O B-party_size_number O O B-restaurant_type O O B-cuisine O B-city O B-timeRange I-timeRange I-timeRange I-timeRange
180
+ O O B-restaurant_type O B-party_size_number O O B-facility O O B-country
181
+ O O O O B-timeRange I-timeRange O B-poi I-poi I-poi I-poi I-poi I-poi B-spatial_relation I-spatial_relation I-spatial_relation O B-party_size_number
182
+ O O O O O O O B-restaurant_type O O B-facility O O B-country
183
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184
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185
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186
+ O O O O O B-restaurant_type O B-city O B-timeRange I-timeRange I-timeRange O B-party_size_number O
187
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188
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189
+ O O O O O B-restaurant_type O B-party_size_number O O B-city B-state
190
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191
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192
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193
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194
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195
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197
+ O O O O O O O O B-party_size_number O O B-restaurant_type O B-country I-country I-country
198
+ O O O O O B-cuisine B-restaurant_type O B-timeRange I-timeRange B-spatial_relation B-city O B-party_size_number O
199
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200
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201
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202
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203
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204
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205
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206
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207
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208
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209
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210
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213
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214
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215
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216
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217
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218
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219
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220
+ O O O B-condition_description O O B-geographic_poi I-geographic_poi I-geographic_poi
221
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222
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223
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224
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225
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226
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227
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228
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229
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230
+ O O O O O O O B-timeRange I-timeRange B-spatial_relation B-country
231
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232
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233
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234
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235
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236
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237
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238
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239
+ O O O O O B-current_location
240
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241
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242
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243
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244
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245
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246
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247
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248
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249
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250
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251
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252
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253
+ O O O B-condition_description O O O B-current_location I-current_location O O B-timeRange I-timeRange I-timeRange
254
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255
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256
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257
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258
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259
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260
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261
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262
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263
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264
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265
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267
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268
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269
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270
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271
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272
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273
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275
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276
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277
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278
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280
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283
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284
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285
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286
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287
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288
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289
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294
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295
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296
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297
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+ O O O B-artist I-artist O O B-year
379
+ O O B-service I-service O O O B-playlist I-playlist I-playlist I-playlist I-playlist
380
+ O O B-playlist I-playlist I-playlist I-playlist I-playlist O
381
+ O O B-music_item O B-artist I-artist
382
+ O O O O O O O B-genre I-genre O O
383
+ O O O B-year B-music_item
384
+ O B-album I-album I-album I-album I-album O B-artist I-artist O O O
385
+ O O O B-music_item O B-artist I-artist I-artist
386
+ O O B-sort B-artist I-artist O B-service
387
+ O O B-service
388
+ O B-genre I-genre
389
+ O O O O B-music_item O O B-service O B-artist I-artist I-artist
390
+ O O B-music_item O B-artist I-artist O B-year
391
+ O O B-genre I-genre
392
+ O O B-artist I-artist O O B-year
393
+ O O O B-service
394
+ O O O B-artist I-artist I-artist I-artist
395
+ O O O B-artist I-artist O
396
+ O O O B-sort B-artist I-artist O B-service
397
+ O O O B-music_item I-music_item O O B-year O O O B-service
398
+ O B-album I-album I-album O B-artist I-artist
399
+ O B-track I-track O B-service
400
+ O B-playlist I-playlist
401
+ O B-object_select B-object_type B-rating_value O O B-best_rating B-rating_unit
402
+ O B-object_select B-object_type B-rating_value B-rating_unit
403
+ O B-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value O O B-best_rating B-rating_unit
404
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value O O B-best_rating B-rating_unit
405
+ O B-rating_value B-rating_unit O B-object_name I-object_name I-object_name I-object_name
406
+ O B-object_select B-object_type O O O B-rating_value
407
+ O O B-object_select B-object_part_of_series_type B-rating_value O B-best_rating B-rating_unit
408
+ O B-rating_value O O B-best_rating B-rating_unit O B-object_name I-object_name I-object_name B-object_part_of_series_type
409
+ O B-rating_value B-rating_unit O O B-best_rating O B-object_name I-object_name
410
+ O B-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value
411
+ O O B-object_select B-object_part_of_series_type B-rating_value B-rating_unit
412
+ O B-object_select B-object_type O B-rating_value O O B-best_rating
413
+ O O B-object_select B-object_type B-rating_value O B-best_rating B-rating_unit
414
+ O B-object_select B-object_type O B-rating_value
415
+ O B-rating_value O O B-best_rating O O B-object_select B-object_type
416
+ O B-object_select B-object_type B-rating_value B-rating_unit
417
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_part_of_series_type B-rating_value B-rating_unit
418
+ O O B-object_select B-object_type B-rating_value B-rating_unit
419
+ O O B-object_select B-object_type B-rating_value B-rating_unit
420
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
421
+ O B-object_name I-object_name B-rating_value O B-best_rating B-rating_unit
422
+ O B-object_select B-object_type B-rating_value O O B-best_rating
423
+ O O B-object_name B-object_part_of_series_type B-rating_value B-rating_unit
424
+ B-object_name I-object_name I-object_name I-object_name I-object_name B-object_part_of_series_type O B-rating_value B-rating_unit O O B-best_rating O O O
425
+ O B-object_name I-object_name I-object_name I-object_name O B-rating_value O O B-best_rating O
426
+ B-object_name I-object_name I-object_name O O O B-rating_value
427
+ O B-rating_value B-rating_unit O B-object_select B-object_type
428
+ O O B-object_select B-object_type O B-rating_value O O B-best_rating B-rating_unit
429
+ O O B-object_type B-object_name I-object_name I-object_name B-rating_value O O B-best_rating
430
+ O B-object_name I-object_name B-rating_value O O B-best_rating
431
+ O O B-object_part_of_series_type B-object_select B-rating_value O
432
+ O B-object_select B-object_type O O O B-rating_value
433
+ O O B-object_select B-object_type B-rating_value O O B-best_rating
434
+ O O B-object_select B-object_type O B-rating_value
435
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
436
+ O B-object_select I-object_select B-object_type B-rating_value O O B-best_rating
437
+ O B-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value O O B-best_rating O
438
+ O B-object_select B-object_type B-rating_value O O B-best_rating B-rating_unit
439
+ O O B-object_select B-object_type B-rating_value B-rating_unit
440
+ O O B-object_select B-object_type B-rating_value O O B-best_rating B-rating_unit
441
+ O B-object_select I-object_select B-object_type B-rating_value B-rating_unit
442
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value O O B-best_rating B-rating_unit
443
+ O B-object_select B-object_type B-rating_value O O B-best_rating B-rating_unit
444
+ O B-object_name I-object_name I-object_name B-rating_value O O B-best_rating B-rating_unit
445
+ O O B-object_select B-object_type B-rating_value O B-best_rating B-rating_unit
446
+ O B-object_select B-object_type B-rating_value B-rating_unit
447
+ O B-rating_value O O B-best_rating B-rating_unit O B-object_select B-object_type
448
+ O O O O B-rating_value O B-object_name
449
+ O B-object_name B-rating_value O O B-best_rating B-rating_unit
450
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit O O B-best_rating
451
+ O B-object_name I-object_name I-object_name B-rating_value O O B-best_rating B-rating_unit
452
+ O B-rating_value B-rating_unit O B-object_name I-object_name I-object_name
453
+ O O B-object_select B-object_type O B-rating_value O B-best_rating
454
+ O B-object_name I-object_name B-rating_value O O B-best_rating B-rating_unit
455
+ O O B-object_select B-object_part_of_series_type O B-rating_value
456
+ O B-rating_value O B-best_rating B-rating_unit O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
457
+ O B-rating_value O O B-best_rating B-rating_unit O B-object_select B-object_type
458
+ O B-object_select B-object_type B-rating_value B-rating_unit
459
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value O O B-best_rating
460
+ O B-object_select B-object_type B-rating_value O O B-best_rating B-rating_unit
461
+ O B-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
462
+ O B-object_name I-object_name I-object_name B-rating_value O B-best_rating B-rating_unit
463
+ O B-object_select B-object_type O B-rating_value
464
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
465
+ O O B-object_select B-object_type O O O B-rating_value
466
+ O B-rating_value B-rating_unit O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
467
+ O O B-rating_value O O B-object_name I-object_name I-object_name
468
+ O B-object_select B-object_part_of_series_type B-rating_value B-rating_unit
469
+ O B-object_name I-object_name I-object_name I-object_name I-object_name O O O B-rating_value B-rating_unit
470
+ O B-object_select B-object_part_of_series_type B-rating_value O O B-best_rating
471
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
472
+ O B-object_name B-rating_value O O B-best_rating
473
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value O O B-best_rating
474
+ O B-rating_value O O O B-object_select B-object_type
475
+ O B-object_select B-object_part_of_series_type O B-rating_value O
476
+ O B-object_select B-object_type O B-rating_value
477
+ O O B-best_rating O B-object_name I-object_name I-object_name O B-rating_value
478
+ O B-rating_value O B-best_rating B-rating_unit O B-object_name I-object_name
479
+ O B-object_name I-object_name I-object_name B-object_part_of_series_type O B-rating_value
480
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value O O B-best_rating B-rating_unit
481
+ O O O B-object_name I-object_name I-object_name I-object_name B-rating_value O O B-best_rating B-rating_unit
482
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
483
+ O B-rating_value O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
484
+ O B-rating_value O O B-best_rating O O O B-object_select B-object_type
485
+ O O B-object_select B-object_part_of_series_type B-rating_value O B-best_rating B-rating_unit
486
+ O B-object_name I-object_name I-object_name I-object_name O B-rating_value
487
+ O B-object_select B-object_type B-rating_value B-rating_unit
488
+ O B-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
489
+ O B-object_name I-object_name O B-rating_value
490
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value O O B-best_rating B-rating_unit
491
+ O B-object_select B-object_type O B-rating_value
492
+ O O B-object_select B-object_type B-rating_value O O B-best_rating
493
+ O B-object_select B-object_type B-rating_value O O B-best_rating B-rating_unit
494
+ O B-object_name I-object_name I-object_name B-rating_value B-rating_unit
495
+ O B-object_select B-object_part_of_series_type B-rating_value O O B-best_rating
496
+ O B-object_name I-object_name I-object_name I-object_name I-object_name O O O B-rating_value B-rating_unit
497
+ O B-object_select B-object_type B-rating_value B-rating_unit O O B-best_rating
498
+ O O B-object_name I-object_name B-rating_value O O B-best_rating
499
+ O B-rating_value B-rating_unit O B-object_name I-object_name I-object_name
500
+ O O B-object_select B-object_part_of_series_type B-rating_value B-rating_unit
501
+ O O O O B-object_type O B-object_name I-object_name
502
+ O O O O B-object_type I-object_type B-object_name
503
+ O O O B-object_name I-object_name I-object_name B-object_type I-object_type
504
+ O O O O B-object_type B-object_name I-object_name I-object_name
505
+ O O O O B-object_type O O O B-object_name I-object_name I-object_name
506
+ O O O B-object_type O B-object_name I-object_name
507
+ O O O O O O B-object_name I-object_name I-object_name I-object_name I-object_name
508
+ O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
509
+ O O O O O B-object_name I-object_name I-object_name
510
+ O O O B-object_type O B-object_name I-object_name
511
+ O O O O O O B-object_name I-object_name
512
+ O O B-object_type I-object_type B-object_name I-object_name
513
+ O O O O O O B-object_type B-object_name I-object_name
514
+ O O O O B-object_name I-object_name I-object_name B-object_type
515
+ O O O O B-object_type I-object_type B-object_name I-object_name I-object_name I-object_name
516
+ O O O O O B-object_name I-object_name
517
+ O O O O O B-object_name I-object_name I-object_name I-object_name B-object_type I-object_type
518
+ O O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
519
+ O O O O B-object_type I-object_type B-object_name I-object_name I-object_name I-object_name
520
+ O O O O B-object_name I-object_name
521
+ O O O B-object_name
522
+ O O O O O B-object_name I-object_name B-object_type I-object_type
523
+ O O O O B-object_type B-object_name I-object_name I-object_name
524
+ O O O O B-object_type I-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
525
+ O O O B-object_name I-object_name
526
+ O O O B-object_name I-object_name I-object_name B-object_type I-object_type
527
+ O O O B-object_type O B-object_name I-object_name
528
+ O O O O B-object_name I-object_name B-object_type
529
+ O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
530
+ O O O B-object_type I-object_type O B-object_name I-object_name
531
+ O O B-object_name I-object_name
532
+ O O O B-object_type I-object_type B-object_name I-object_name I-object_name
533
+ O O O O B-object_name I-object_name I-object_name
534
+ O O O O O B-object_name I-object_name B-object_type
535
+ O O O B-object_name I-object_name B-object_type
536
+ O O O O O O O B-object_name I-object_name I-object_name
537
+ O O O O B-object_type O B-object_name I-object_name I-object_name I-object_name
538
+ O O O O B-object_name I-object_name B-object_type
539
+ O O O B-object_type O B-object_name I-object_name I-object_name
540
+ O O O B-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
541
+ O O O O O B-object_name I-object_name B-object_type
542
+ O O O O B-object_type I-object_type B-object_name I-object_name
543
+ O O O B-object_type I-object_type B-object_name I-object_name I-object_name
544
+ O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
545
+ O O O O B-object_name I-object_name B-object_type
546
+ O O O O O B-object_name I-object_name B-object_type
547
+ O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
548
+ O O O O B-object_name I-object_name
549
+ O O O O O B-object_name I-object_name I-object_name I-object_name I-object_name
550
+ O O O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type I-object_type
551
+ O O O O O O B-object_name I-object_name B-object_type
552
+ O O O O O O B-object_name I-object_name I-object_name I-object_name I-object_name
553
+ O O O O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
554
+ O O O B-object_name
555
+ O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
556
+ O O O B-object_type O O O B-object_name I-object_name I-object_name I-object_name O
557
+ O O O B-object_type O O O O B-object_name I-object_name I-object_name I-object_name I-object_name
558
+ O O O O B-object_name I-object_name B-object_type
559
+ O O O O O B-object_name I-object_name I-object_name B-object_type
560
+ O O O O B-object_name I-object_name B-object_type
561
+ O O O B-object_type B-object_name I-object_name I-object_name I-object_name
562
+ O O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
563
+ O O O O O B-object_name I-object_name I-object_name B-object_type
564
+ O O O B-object_type B-object_name I-object_name I-object_name
565
+ O O O B-object_name I-object_name I-object_name B-object_type
566
+ O O B-object_type B-object_name I-object_name I-object_name I-object_name
567
+ O O O O B-object_type O O O B-object_name I-object_name I-object_name
568
+ O O O B-object_type I-object_type B-object_name I-object_name
569
+ O O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
570
+ O O O B-object_type O O O B-object_name I-object_name
571
+ O O O O B-object_name B-object_type
572
+ O O O B-object_type B-object_name I-object_name I-object_name I-object_name
573
+ O O O O B-object_name I-object_name
574
+ O B-object_name I-object_name
575
+ O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
576
+ O O O O B-object_type I-object_type B-object_name I-object_name I-object_name I-object_name
577
+ O O O O O B-object_name I-object_name I-object_name I-object_name
578
+ O O O B-object_type O O O O B-object_name I-object_name I-object_name I-object_name
579
+ O O O B-object_type B-object_name I-object_name
580
+ O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
581
+ O O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
582
+ O O B-object_type I-object_type B-object_name I-object_name
583
+ O O O O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
584
+ O O O O B-object_type B-object_name I-object_name I-object_name
585
+ O O O O B-object_type I-object_type O B-object_name I-object_name I-object_name I-object_name
586
+ O O O O B-object_name I-object_name I-object_name I-object_name
587
+ O O O O O B-object_name
588
+ O O O O B-object_name I-object_name I-object_name I-object_name
589
+ O O O O B-object_name I-object_name I-object_name I-object_name B-object_type
590
+ O O O B-object_name I-object_name B-object_type
591
+ O O O B-object_name I-object_name I-object_name I-object_name
592
+ O O O O O O O O B-object_name I-object_name I-object_name I-object_name I-object_name
593
+ O O O O B-object_name I-object_name B-object_type
594
+ O O O B-object_name I-object_name I-object_name B-object_type
595
+ O O O O B-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
596
+ O O O O B-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
597
+ O O O O B-object_name I-object_name B-object_type O O
598
+ O O O O O B-object_name I-object_name B-object_type
599
+ O O O O O B-object_name I-object_name
600
+ O O O B-object_type B-object_name I-object_name
601
+ O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O
602
+ O B-movie_name I-movie_name O
603
+ O B-movie_name I-movie_name I-movie_name O O B-timeRange I-timeRange
604
+ O O O B-object_type I-object_type
605
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
606
+ O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O O O B-object_location_type
607
+ O O O B-object_type O B-movie_name I-movie_name I-movie_name
608
+ O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O B-timeRange I-timeRange I-timeRange
609
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O O B-spatial_relation B-object_location_type
610
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
611
+ O O O O O B-object_location_type I-object_location_type O B-movie_name I-movie_name I-movie_name B-spatial_relation O O
612
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name O O B-spatial_relation B-object_location_type I-object_location_type
613
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name O O O O O
614
+ O O B-object_type O B-movie_name I-movie_name O B-location_name I-location_name
615
+ O O O B-object_type I-object_type O O O B-location_name
616
+ O O O B-movie_type O B-spatial_relation I-spatial_relation I-spatial_relation
617
+ O B-movie_name I-movie_name O B-timeRange I-timeRange I-timeRange I-timeRange I-timeRange
618
+ O O B-movie_type I-movie_type B-spatial_relation I-spatial_relation I-spatial_relation O B-timeRange O
619
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name O O B-object_location_type I-object_location_type
620
+ O O O B-movie_name I-movie_name I-movie_name B-timeRange I-timeRange I-timeRange
621
+ O O B-movie_type I-movie_type O B-location_name I-location_name
622
+ O O O B-object_type O B-movie_name I-movie_name I-movie_name
623
+ O O O O O O O O B-movie_type O B-spatial_relation I-spatial_relation I-spatial_relation
624
+ O B-movie_name I-movie_name I-movie_name I-movie_name O O B-location_name I-location_name
625
+ O O B-spatial_relation B-object_location_type I-object_location_type O O B-movie_name
626
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name O B-location_name I-location_name I-location_name
627
+ O B-movie_name I-movie_name O B-timeRange I-timeRange I-timeRange I-timeRange O O B-spatial_relation B-object_location_type
628
+ O O O B-spatial_relation B-object_location_type I-object_location_type O B-movie_name I-movie_name O O B-timeRange
629
+ O B-movie_name I-movie_name I-movie_name O O B-location_name I-location_name
630
+ O O B-object_type I-object_type O O B-location_name I-location_name
631
+ O O O B-object_type I-object_type B-spatial_relation
632
+ O O B-object_type O O B-location_name I-location_name I-location_name
633
+ O O O B-movie_type O B-location_name I-location_name
634
+ O B-movie_type O B-location_name I-location_name
635
+ O O O B-object_type I-object_type
636
+ O O O O B-object_type I-object_type
637
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name
638
+ O O O O B-object_type O B-movie_type B-spatial_relation I-spatial_relation I-spatial_relation
639
+ O O O O B-object_type I-object_type O B-location_name I-location_name
640
+ O B-movie_type I-movie_type B-spatial_relation I-spatial_relation
641
+ O B-movie_name I-movie_name O O B-location_name I-location_name
642
+ O O O B-object_type I-object_type B-spatial_relation I-spatial_relation I-spatial_relation
643
+ O O B-object_type O B-location_name I-location_name I-location_name
644
+ O O O O B-movie_name O O B-spatial_relation B-object_location_type I-object_location_type
645
+ O O O B-object_type I-object_type O B-location_name I-location_name
646
+ O O B-movie_type B-spatial_relation I-spatial_relation I-spatial_relation
647
+ O O B-object_type I-object_type B-spatial_relation I-spatial_relation I-spatial_relation
648
+ O O O B-spatial_relation B-object_location_type I-object_location_type O O B-movie_type
649
+ O B-movie_type O O B-timeRange O O B-spatial_relation B-object_location_type
650
+ O B-movie_name I-movie_name I-movie_name O
651
+ O O O O O B-location_name I-location_name B-object_type I-object_type
652
+ O O B-movie_name I-movie_name I-movie_name I-movie_name O O O B-spatial_relation B-object_location_type
653
+ O O B-object_type I-object_type O B-location_name I-location_name
654
+ O O B-movie_type O B-location_name I-location_name
655
+ O O B-movie_type I-movie_type O B-spatial_relation I-spatial_relation I-spatial_relation
656
+ O O O O B-movie_name I-movie_name
657
+ O O B-location_name I-location_name B-object_type I-object_type
658
+ O B-movie_name I-movie_name O O B-timeRange
659
+ O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O O B-location_name I-location_name
660
+ O O B-object_type I-object_type O B-location_name I-location_name I-location_name
661
+ O O O O B-movie_name I-movie_name
662
+ O O B-object_type O B-location_name I-location_name
663
+ O B-movie_name I-movie_name I-movie_name I-movie_name O O O B-timeRange I-timeRange
664
+ O O O B-object_type O B-location_name I-location_name O O B-movie_type I-movie_type
665
+ O O B-object_type O B-movie_name I-movie_name I-movie_name
666
+ O O O B-movie_type B-spatial_relation I-spatial_relation I-spatial_relation
667
+ O B-movie_type O O B-spatial_relation I-spatial_relation
668
+ O B-movie_name I-movie_name I-movie_name O
669
+ O O O B-object_type I-object_type O B-location_name I-location_name I-location_name
670
+ O O B-object_type I-object_type B-spatial_relation I-spatial_relation
671
+ O O O O B-movie_name
672
+ O O O B-object_type O O B-movie_name I-movie_name I-movie_name O B-object_location_type I-object_location_type
673
+ O O B-object_type O B-movie_name I-movie_name I-movie_name I-movie_name O B-location_name I-location_name
674
+ O O B-object_type I-object_type O B-location_name I-location_name I-location_name
675
+ O O O B-object_type I-object_type B-spatial_relation I-spatial_relation I-spatial_relation
676
+ O O O B-object_type I-object_type O B-movie_type B-spatial_relation
677
+ O O B-object_type I-object_type O B-movie_type I-movie_type B-spatial_relation I-spatial_relation I-spatial_relation
678
+ O B-movie_name I-movie_name I-movie_name I-movie_name O O B-location_name I-location_name I-location_name
679
+ O O O O O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
680
+ O B-movie_name I-movie_name I-movie_name I-movie_name O O O B-object_location_type I-object_location_type
681
+ O B-object_type O B-movie_name I-movie_name I-movie_name O O O O B-object_location_type
682
+ O O B-movie_name I-movie_name I-movie_name B-object_type O O B-spatial_relation B-object_location_type I-object_location_type
683
+ O O O B-spatial_relation I-spatial_relation B-movie_type I-movie_type O
684
+ B-object_type I-object_type B-spatial_relation I-spatial_relation O B-movie_type I-movie_type
685
+ O B-movie_type O O B-spatial_relation I-spatial_relation
686
+ O O B-object_type I-object_type B-spatial_relation I-spatial_relation I-spatial_relation
687
+ O B-movie_name I-movie_name O
688
+ O B-movie_name I-movie_name O O O B-spatial_relation B-object_location_type I-object_location_type O B-timeRange
689
+ O O O B-object_type I-object_type
690
+ O O O O O B-object_type I-object_type
691
+ O O B-object_type I-object_type O B-location_name I-location_name I-location_name B-timeRange I-timeRange I-timeRange
692
+ O O B-spatial_relation B-object_location_type O B-movie_type O
693
+ O O O B-object_type I-object_type
694
+ O O O B-object_type O B-movie_name I-movie_name I-movie_name
695
+ O B-movie_type O O B-spatial_relation I-spatial_relation
696
+ O O B-object_location_type O B-movie_name I-movie_name I-movie_name I-movie_name
697
+ O O O B-object_type I-object_type O B-movie_type I-movie_type B-spatial_relation I-spatial_relation I-spatial_relation
698
+ O O O B-object_type I-object_type O B-location_name I-location_name I-location_name
699
+ O O B-object_type O B-movie_name I-movie_name I-movie_name I-movie_name O B-location_name I-location_name
700
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O O B-object_location_type
JointBERT-master/data/snips/intent_label.txt ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ UNK
2
+ AddToPlaylist
3
+ BookRestaurant
4
+ GetWeather
5
+ PlayMusic
6
+ RateBook
7
+ SearchCreativeWork
8
+ SearchScreeningEvent
JointBERT-master/data/snips/slot_label.txt ADDED
@@ -0,0 +1,74 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ PAD
2
+ UNK
3
+ O
4
+ B-album
5
+ I-album
6
+ B-artist
7
+ I-artist
8
+ B-best_rating
9
+ B-city
10
+ I-city
11
+ B-condition_description
12
+ B-condition_temperature
13
+ B-country
14
+ I-country
15
+ B-cuisine
16
+ I-cuisine
17
+ B-current_location
18
+ I-current_location
19
+ B-entity_name
20
+ I-entity_name
21
+ B-facility
22
+ I-facility
23
+ B-genre
24
+ I-genre
25
+ B-geographic_poi
26
+ I-geographic_poi
27
+ B-location_name
28
+ I-location_name
29
+ B-movie_name
30
+ I-movie_name
31
+ B-movie_type
32
+ I-movie_type
33
+ B-music_item
34
+ I-music_item
35
+ B-object_location_type
36
+ I-object_location_type
37
+ B-object_name
38
+ I-object_name
39
+ B-object_part_of_series_type
40
+ I-object_part_of_series_type
41
+ B-object_select
42
+ I-object_select
43
+ B-object_type
44
+ I-object_type
45
+ B-party_size_description
46
+ I-party_size_description
47
+ B-party_size_number
48
+ B-playlist
49
+ I-playlist
50
+ B-playlist_owner
51
+ I-playlist_owner
52
+ B-poi
53
+ I-poi
54
+ B-rating_unit
55
+ B-rating_value
56
+ B-restaurant_name
57
+ I-restaurant_name
58
+ B-restaurant_type
59
+ I-restaurant_type
60
+ B-served_dish
61
+ I-served_dish
62
+ B-service
63
+ I-service
64
+ B-sort
65
+ I-sort
66
+ B-spatial_relation
67
+ I-spatial_relation
68
+ B-state
69
+ I-state
70
+ B-timeRange
71
+ I-timeRange
72
+ B-track
73
+ I-track
74
+ B-year
JointBERT-master/data/snips/test/label ADDED
@@ -0,0 +1,700 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ AddToPlaylist
2
+ BookRestaurant
3
+ AddToPlaylist
4
+ GetWeather
5
+ PlayMusic
6
+ SearchScreeningEvent
7
+ BookRestaurant
8
+ GetWeather
9
+ SearchScreeningEvent
10
+ BookRestaurant
11
+ SearchScreeningEvent
12
+ SearchCreativeWork
13
+ SearchScreeningEvent
14
+ BookRestaurant
15
+ SearchCreativeWork
16
+ GetWeather
17
+ SearchCreativeWork
18
+ BookRestaurant
19
+ SearchScreeningEvent
20
+ BookRestaurant
21
+ RateBook
22
+ AddToPlaylist
23
+ AddToPlaylist
24
+ SearchScreeningEvent
25
+ GetWeather
26
+ GetWeather
27
+ SearchScreeningEvent
28
+ BookRestaurant
29
+ PlayMusic
30
+ AddToPlaylist
31
+ AddToPlaylist
32
+ RateBook
33
+ PlayMusic
34
+ SearchScreeningEvent
35
+ AddToPlaylist
36
+ SearchCreativeWork
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+ RateBook
38
+ SearchScreeningEvent
39
+ GetWeather
40
+ GetWeather
41
+ PlayMusic
42
+ RateBook
43
+ PlayMusic
44
+ GetWeather
45
+ PlayMusic
46
+ GetWeather
47
+ PlayMusic
48
+ RateBook
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+ BookRestaurant
50
+ BookRestaurant
51
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52
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53
+ SearchCreativeWork
54
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55
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56
+ BookRestaurant
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+ RateBook
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66
+ SearchScreeningEvent
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68
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69
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71
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73
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80
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85
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86
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+ GetWeather
88
+ AddToPlaylist
89
+ AddToPlaylist
90
+ SearchScreeningEvent
91
+ AddToPlaylist
92
+ PlayMusic
93
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94
+ AddToPlaylist
95
+ AddToPlaylist
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97
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98
+ AddToPlaylist
99
+ AddToPlaylist
100
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102
+ PlayMusic
103
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104
+ AddToPlaylist
105
+ SearchScreeningEvent
106
+ RateBook
107
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108
+ PlayMusic
109
+ AddToPlaylist
110
+ SearchScreeningEvent
111
+ PlayMusic
112
+ AddToPlaylist
113
+ GetWeather
114
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115
+ GetWeather
116
+ GetWeather
117
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118
+ SearchCreativeWork
119
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120
+ AddToPlaylist
121
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122
+ GetWeather
123
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124
+ RateBook
125
+ RateBook
126
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127
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128
+ GetWeather
129
+ BookRestaurant
130
+ SearchScreeningEvent
131
+ GetWeather
132
+ SearchScreeningEvent
133
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135
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136
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142
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143
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145
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146
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147
+ GetWeather
148
+ GetWeather
149
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150
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153
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154
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155
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156
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189
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191
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207
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217
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219
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220
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221
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222
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226
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228
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230
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231
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234
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235
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237
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+ BookRestaurant
243
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245
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246
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247
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+ PlayMusic
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252
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253
+ GetWeather
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255
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256
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260
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262
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263
+ GetWeather
264
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265
+ GetWeather
266
+ GetWeather
267
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268
+ PlayMusic
269
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270
+ GetWeather
271
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272
+ AddToPlaylist
273
+ BookRestaurant
274
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275
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276
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277
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279
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281
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283
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284
+ GetWeather
285
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286
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287
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289
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292
+ AddToPlaylist
293
+ AddToPlaylist
294
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295
+ SearchScreeningEvent
296
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297
+ SearchScreeningEvent
298
+ RateBook
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300
+ AddToPlaylist
301
+ AddToPlaylist
302
+ SearchScreeningEvent
303
+ SearchScreeningEvent
304
+ AddToPlaylist
305
+ GetWeather
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+ GetWeather
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+ GetWeather
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316
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324
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329
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345
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395
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402
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1
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+ play signe anderson chant music that is newest
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+ what s the weather here on 2/7/2021
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23
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55
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56
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57
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58
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59
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60
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61
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62
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63
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64
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66
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68
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69
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70
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71
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72
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73
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74
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76
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77
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78
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80
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81
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82
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83
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84
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85
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86
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87
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88
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89
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90
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91
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92
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93
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94
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95
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96
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100
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101
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102
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103
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104
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105
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106
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107
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108
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112
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113
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114
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115
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116
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117
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118
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119
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120
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121
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123
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124
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125
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126
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127
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128
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129
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130
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131
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132
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133
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134
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135
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136
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137
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138
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139
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140
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141
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142
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143
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144
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145
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146
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148
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149
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150
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151
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152
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153
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154
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155
+ can you add a track to my spain top 50 playlist
156
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157
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158
+ add mary wells sings my guy to the electro sur playlist
159
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160
+ book a table around london borough of ealing that is highly rated in a gluten free bar
161
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162
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163
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166
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167
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168
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170
+ what is the local movie schedule
171
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172
+ i d like to know what movies are on the movie schedules nearby
173
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174
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175
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176
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177
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178
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179
+ the last hawk gets a total of 3 out of 6 stars from me
180
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181
+ play pop 2017 picks
182
+ play some theme songs from 1974
183
+ what will the weather be in la at 9 o clock
184
+ can you add xanadu to latin alternative music
185
+ can you find me the naked city – justice with a bullet album
186
+ please search the work eve-olution
187
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188
+ add this artist to the laugh list
189
+ i d like to eat at a restaurant around china with a party of 7 anywhere that serves ouzeri
190
+ the sleep machine waterscapes playlist needs some kris chetan ramlu in it
191
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192
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193
+ my rating for the eiffel tower and other mythologies is 0 out of 6 stars
194
+ i d like a table for midday at the unseen bean
195
+ where can i see the movie across the line: the exodus of charlie wright
196
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197
+ what are the movie schedules
198
+ i want a table for me and my kids in turkey at a neighboring restaurant
199
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200
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202
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203
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204
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205
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206
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207
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208
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+ find the schedule for the band of honest men at the nearest movie theatre
210
+ what will the weather be in waverly city brazil on purple heart day
211
+ what is the weather forecast in delaware
212
+ play a top-50 tune from 1982
213
+ play shinji miyazaki s music on netflix
214
+ can i get the game list of mew singles
215
+ what s the forecast for belize around meal time
216
+ add gary lachman track to jazz for loving couples playlist
217
+ find the path to power
218
+ put artist paulinho da costa on my very nearly nashville playlist
219
+ i am looking for the work: nikki
220
+ what s the weather in low moor
221
+ play some nineties music
222
+ find a television show called swing high
223
+ use netflix to play bizzy bone kiss me goodnight sergeant major
224
+ i d like to see movie schedules for kerasotes theatres
225
+ i want these are the days added to my spotlight spain 2016 playlist
226
+ play the greatest soundtrack by nhat son on last fm
227
+ what is the tv series in app store
228
+ book the space aliens grill & bar in hord wy for feb the twenty-seventh
229
+ find a saga called set sail the prairie
230
+ can jovino santos neto s album get added to my confidence boost playlist
231
+ show animated movies in nearest movie theatre
232
+ find the game company of heroes
233
+ where can i find paranormal activity 3 playing near me 1 hour from now
234
+ book a table this evening in saint vincent and the grenadines at a gastropub
235
+ can i listen to dj vibe s top 10
236
+ what films are at the nearest cinema
237
+ what is the weather like in north salt lake and afghanistan
238
+ can you tell me the actors of the saga awards/
239
+ go to my all out 00s and add brian wilson
240
+ food truck in panama for five
241
+ look up the movie schedule
242
+ book a table for chasity ruiz and mary at the fat duck in puerto rico
243
+ find the gill deacon show
244
+ find the movie schedule for films in the area
245
+ will i be able to watch camping-car at movie house at 6 pm
246
+ play how does it work by helen carter
247
+ what s the weather like in schenectady ma
248
+ play some folk-rock music
249
+ give this current book zero out of 6
250
+ rate this album 5 points
251
+ how is the weather right now at my current place
252
+ play sixties music by giovanni battista guadagnini
253
+ tell me the weather forecast close by brown county state park for meal time
254
+ play the last wellman braud album relaesd
255
+ play sugar baby by frank beard
256
+ find the schedule for the solitude of prime numbers at the nearest cinema in 1 hour
257
+ play the discografia de the pretty reckless saga
258
+ i want to give the current textbook 0 out of 6 stars
259
+ show me movie times for animated movies playing three hours from now in the neighbourhood
260
+ find the game just dance greatest hits
261
+ add this track to the sin ti playlist
262
+ show me the closest movie house playing an unfinished life at eight pm
263
+ what s it like in bahrain right now
264
+ can you add blood on the face to the playlist called heartland country
265
+ on jan the twentieth what will it feel like in ct or the area not far from it
266
+ i need a table in uruguay in 213 days when it s chillier
267
+ add this track by horace andy to acoustic soul
268
+ plan an album by roni duani
269
+ add song to siesta
270
+ can you tell me the weather forecast for samoa
271
+ play music on youtube
272
+ add spirit touches ground to my leche con chocolate list
273
+ i need a table for 1 minute from now at any pub for five around in that also serves fisn n chips
274
+ book a spot at the food truck in ma
275
+ 21 weeks from now elinor crystal turner and nita want to eat german food at a bar in distant california
276
+ find a tv show called ruthless
277
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278
+ book a spot for 7 at an outdoor food court in denmark
279
+ i would rate the persistence of vision 1 stars and a best rating of 6
280
+ i need a reservation for february 27 2020 at a bar that serves paté
281
+ find the ghost of tom joad
282
+ i need a reservation for ten at a tavern in west virginia
283
+ what time is children of divorce playing
284
+ will there be a blizzard in white house curacao
285
+ play the top melody from artist maakii
286
+ are any animated movies playing at magic johnson theatres
287
+ give the current album a five
288
+ i want to add digital line to my playlist called infantil
289
+ the current essay gets four points
290
+ what will the weather be in grand coteau ut at six pm
291
+ can you find me a trailer for phineas redux
292
+ add the singer ivan roudyk to my fairy tales playlists
293
+ add song in my playlist dance workout
294
+ what movies can i see in the area
295
+ tell me what films are playing at plitt theatres
296
+ add in the heart of the world to the epic gaming playlist
297
+ find movie times
298
+ rate the book english grammar in use a five
299
+ play tujiko noriko s ten years and running
300
+ add the song to the soundscapes for gaming playlist
301
+ can you put a song by jessica mauboy on my playlist entitled a sudden rainstorm
302
+ show movie schedule
303
+ show me movie schedules for today
304
+ add cecil womack to my 50 great female voices playlist
305
+ will it be freezing here in 9 seconds
306
+ forecast for serbia
307
+ i want to give a mortal flower a two
308
+ where can i view the picture reaching horizons
309
+ in hawaii will it be warmer at 3 am
310
+ rate the little book four stars
311
+ rate the current textbook one of 6 stars
312
+ i want a table for five at a restaurant with latin food in arkansas for 1 hour from now
313
+ find love will tear us apart a photograph
314
+ please play me a popular track from 1984
315
+ book a mediterranean restaurant for my sister and i
316
+ how will the weather be different 5 years from now in waconia
317
+ search for teenage mutant hero turtles: fall of the foot clan photograph
318
+ play party anthems
319
+ what is the niceville forecast in fm
320
+ find heat wave
321
+ which is the nearest movie house playing the diary of anne frank
322
+ can i have the movie schedule for imax corporation
323
+ book me a reservation for eight for the top-rated bakery eleven hours from now in mango
324
+ play yung joc on slacker
325
+ show 50 words for snow creative picture
326
+ play the electrochemical and solid state letters song
327
+ table for 8 at a popular food court
328
+ find me a table for 8 people at a nearby al restaurant one minute from now
329
+ is there rain now in maine
330
+ show me the photograph johnny cash: the complete columbia album collection
331
+ find movie schedules
332
+ find movie schedules for united paramount theatres
333
+ what is the forecast for montana at dinner
334
+ please add this track to my de camino playlist
335
+ book me a restaurant please
336
+ find drumline: a new beat a picture
337
+ play the red room sessions from chris cunningham
338
+ play the great adventures of slick rick game
339
+ list movie schedules for movies playing close by
340
+ i am looking for the tv show called the flight of the lost balloon
341
+ add david axelrod to my futuros hits list
342
+ play me sun ra songs from the fifties
343
+ add this track to my dinnertime acoustics playist
344
+ add tune to atmospheric black metal playlist
345
+ need to see mother joan of the angels in one second
346
+ give 2 out of 6 points to the following textbook
347
+ i would like to book a restaurant for two in 42 weeks from now in wagram
348
+ play some last fm music like the 1992 ep from peaches
349
+ where is the closest cinema playing a drink in the passage
350
+ i m hoping you can find a photograph from live at the isle of wight 1970
351
+ what movies are around here
352
+ book a restaurant distant from downtown
353
+ find doggy day school an album
354
+ please play bitch please ii
355
+ find a video game called young
356
+ is strauss is playing today at the cineplex odeon corporation
357
+ award this current novel 0 points
358
+ weather for this winter here
359
+ what animated movies are playing at the closest movie theatre
360
+ rate this book four of 6 points
361
+ i want to go see the trouble with girls
362
+ cock-a-doodle-doo was awful i m giving it a 0 out of 6
363
+ show me the schedule of films in the neighbourhood
364
+ book a table for nine people in svalbard and jan mayen
365
+ i would give french poets and novelists a best rating of 6 and a value of three
366
+ what animated movies are playing nearby
367
+ will there be a cloud here at 06:50:20
368
+ i want to give the chronicle zombie bums from uranus 3 points
369
+ i d like to know when i can see the taking of flight 847: the uli derickson story at amco entertainment
370
+ play is this my world by leo arnaud
371
+ book a reservation for clinton street baking company & restaurant distant from downtown
372
+ add nyoil to my this is prince playlist
373
+ show me the everybody wants you picture
374
+ find a restaurant in fm that servec quiche
375
+ i would give this current novel 2 stars with a best rating of 6
376
+ i want to book a pastelaria cafe in alabama for me and my great grandfather
377
+ is hail in the weather forecast for monterey bay national marine sanctuary
378
+ add tune to sxsw fresh playlist
379
+ make a reservation in a popular sicilian bar place nearby for me only tomorrow
380
+ i need a table for 9
381
+ add this artist to my post-grunge playlist
382
+ rate this album a 2
383
+ what will the weather be like this tuesday in the area neighboring rendezvous mountain educational state forest
384
+ i need a table in ottoville on feb 15th 2029 at gus stevens seafood restaurant & buccaneer lounge
385
+ i need a table for five at childs restaurants in brunei
386
+ how do i get the game still on it
387
+ i would like to make a reservation for 2 for brunch
388
+ need a table for party of five for december 26 2040 in the state of mt
389
+ book me a restaurant for nine in statham
390
+ i d like a table for ten in 2 minutes at french horn sonning eye
391
+ find a movie house for 07:52 showing ganges: river to heaven
392
+ what is the michael moore is a big fat stupid white man video game
393
+ i want to eat close to bowlegs seven years from now
394
+ for my playlist chill add the name cater fe she
395
+ search for the halfway home tv show
396
+ find movie times
397
+ play journey list
398
+ tell me what animated movies i can see at the closest movie theatre
399
+ i d like to see the trailer tony parker
400
+ what time is holiday heart showing at the movie house
401
+ play the movie white christmas
402
+ is it forecast to be warm in doi inthanon national park
403
+ add this tune to cristina s endorphin rush playlist
404
+ play a song by nash the slash
405
+ i rate doom 3: worlds on fire a 1 of 6
406
+ what time is phil ochs: there but for fortune playing at the movie house
407
+ add andreas johnson to my rock save the queen playlist
408
+ i d like to watch take this waltz
409
+ what are the mann theatres showtimes for secret sunshine
410
+ will there be snowfall in kitlope heritage conservancy
411
+ play geddy lee music on spotify sort by top
412
+ rate in the eyes of mr fury zero of 6
413
+ look up the tv series operace silver a
414
+ i m looking for the tv series called unborn
415
+ play the song memories are my only witness
416
+ i give the phishing manual four stars out of 6
417
+ play clásicos del hip hop español
418
+ add rupee to my ultra metal playlist
419
+ add shi xin hui to my piano chill playlist
420
+ what time is the clutching hand playing at amco entertainment
421
+ add circus to my post garage wave revival list
422
+ the chronicle charlie peace earns 4 stars from me
423
+ find conker: live and reloaded
424
+ show me the nearest movie house showing the luckiest girl in the world
425
+ play track music from peter finestone on netflix sort by newest
426
+ play the song shine a light
427
+ book a popular restaurant of thai cuisine
428
+ which animated movies are playing in the neighbourhood and when
429
+ i want to listen to the song only the greatest
430
+ i d like to eat at the best restaurant
431
+ is it going to be chilly in western sahara in 13 hours
432
+ i want to book a restaurant for four around zapata
433
+ rate if tomorrow comes 2 of 6 stars
434
+ the book history by contract is rated five stars in my opinion
435
+ i want to book a bar in bonaparte palau
436
+ i m looking for dead at 21 the tv series
437
+ can you make reservations at a tea house that serves fettucine
438
+ put a track by lil mama into my guest list sneaky zebra playlist
439
+ put some frank ferrer into my edna st vincent millay playlist
440
+ what is the forecast for niger
441
+ rate this novel a 3
442
+ add this ruth crawford seeger song to my playlist called the soundtrack 007
443
+ is it going to snow next year in wv
444
+ is romulus and the sabines playing at the nearest cinema at ten
445
+ show me the new showings for animated movies in the neighborhood
446
+ play the video game the genesis machine
447
+ i want to go to 88th st-boyd av or close by and book seats for 10
448
+ i need to add to the funk soul disco playlist my favorite artist
449
+ i want to book a cafe for 3 in fargo
450
+ where can i watch tv series shopping spree
451
+ play an andy silvester sound track from the thirties on spotify
452
+ i d like to eat at a popular brasserie in chile with a party of 5
453
+ what s the forecast for my current place at five pm
454
+ give private games 3 stars out of 6
455
+ in 17 minutes will it be foggy in songimvelo game reserve
456
+ how hot will it be in wisconsin on august fourth
457
+ i d like to put qriii onto songs to sing in the car
458
+ will it be chilly in oakdale ok
459
+ add dwele to marguerite s eurovision 2016 playlist
460
+ what s the weather forecast for croatia on jul 25th
461
+ find tv series titled a life in the death of joe meek
462
+ open fadl shaker on spotify and play a melody starting with the newest
463
+ please add jency anthony to my playlist this is mozart
464
+ whats the weather in ga
465
+ i rate the chronicle son of the tree with four of 6 points
466
+ add git to domingo indie
467
+ will there be cloud coverage in verdery myanmar
468
+ rate maps for lost lovers 1 of 6
469
+ will it snow in granbury
470
+ play me a cinder block movement
471
+ find the tv series shaun the sheep
472
+ i want to hear the jody williams sound track
473
+ what is the forecast for foggy conditions here in twenty one minutes
474
+ book a table at grecian coffee house for 7 on apr 7th 2024
475
+ show creative photograph of icewind dale: heart of winter
476
+ rate the manxman 5 out of 6
477
+ add this song to my lo que suena new york playlist
478
+ find reproductions: songs of the human league
479
+ play a 2001 sound track on deezer
480
+ weather for ma in the morning
481
+ play a ballad by bob johnston
482
+ is there a snowstorm in russia
483
+ will it be nice on aug the nineteenth in beda bulgaria
484
+ i d like for you to put this artist to my evening commute playlist
485
+ play the caps lock trailer
486
+ give me the movie schedules for warren theatres
487
+ i need current movie schedules
488
+ add even serpents shine to dorothea s indie hipster playlist
489
+ play ep by arjen anthony lucassen
490
+ give 4 points to this novel
491
+ add star light star bright to my jazz classics playlist
492
+ put nothing remains the same on my summer music playlist
493
+ weather for the night time in new mexico
494
+ add pangaea to my gold edition playlist
495
+ find me a movie with the name oshin
496
+ add ian stuart donaldson to canadian country
497
+ show me movie time for i am sorry at my movie house
498
+ please add ruud jolie to my playlist guest list polygon
499
+ add patti page album to i love my neo soul
500
+ add an album by twink to my classic country playlist
501
+ will it be a snowy day in dalcour
502
+ rate this essay a two out of 6
503
+ find the movie schedules for animated movies nearby at 09:44 am
504
+ add armand van helden to my black sabbath the ozzy years playlist
505
+ give this chronicle a 4
506
+ i m looking for a churrascaria place with wifi that can serve a party of five
507
+ what time is goodbye mothers playing
508
+ book the city tavern in holiday ks
509
+ what movies are playing dickinson theatres
510
+ rate the key word and other mysteries 4 of 6
511
+ i d like to watch may blossom
512
+ play some music on slacker
513
+ i want to rate the ingenuity gap 3 out of 6
514
+ add song to my wild country playlist
515
+ what is the weather forecast for close-by burkina
516
+ i want to watch supernatural: the unseen powers of animals
517
+ listen to dragon ball: music collection
518
+ add troy van leeuwen to my nu metal list
519
+ add born free to fresh r&b
520
+ book at table at forest av restaurant close-by for 2 1 second from now
521
+ can you get me the trailer of the multiversity
522
+ are there movies at malco theatres
523
+ rate the current chronicle series 3 out of 6 points
524
+ can i get the movie times
525
+ i want to add hind etin to my la mejor música dance 2017 playlist
526
+ play some latin on zvooq
527
+ what is the freezing forecast for british virgin islands
528
+ pull up sweeney todd - il diabolico barbiere di fleet street
529
+ put four rating on the raging quiet
530
+ show me the tv show limit of love: umizaru
531
+ which movies are playing at the closest cinema
532
+ add this album by karl davydov to reyna s this is luis fonsi playlist
533
+ where can i see the television show falling away from me
534
+ book me a table for 5 at a best rated restaurant in italy
535
+ will there be a snowstorm in taberville
536
+ add this song to this is no te va gustar playlist
537
+ can i get the movies showtimes for the closest movie house
538
+ do you have something like impossible is nothing by abderrahmane abdelli
539
+ what is the weather forecast for cistern
540
+ please make reservations in yeager for seven am at a highly rated indian brasserie
541
+ play me a nineties sound track
542
+ where can i find thor meets captain america
543
+ i need to have pat alger s album placed onto the spotlight spain 2016 playlist
544
+ can i get the movie times for fox theatres
545
+ i d like to watch wish you were dead
546
+ i d like to watch apocalypse 2024
547
+ show creativity of song a discord electric
548
+ is love and other troubles playing
549
+ show me the current movie times
550
+ rate the lie tree five
551
+ i want to add another album to the wine & dine playlist
552
+ add another tune to my pumping iron playlist
553
+ play a track by mila islam from deezer
554
+ is it rainy season in manitou springs
555
+ give 2 stars to the doom brigade
556
+ add this tune to my dinnertime acoustics list
557
+ what are the current movie schedules
558
+ what is the showtime for arsho
559
+ list movie times at harkins theatres
560
+ what movies are showing in the neighborhood
561
+ play my playlist tgif on itunes
562
+ what will the weather be like on january 2nd 2025 in ga
563
+ what animated movies are playing in the neighbourhood and when
564
+ book a spot at savoy hotel and grill that is neighboring wisconsin
565
+ can you find me the back when i knew it all album
566
+ add george thorogood to el mejor rock en español
567
+ play the album how insensitive
568
+ i m looking for the pokémon: the movie 2000 tv show
569
+ place this tune onto my dinner for 2 playlist
570
+ where can i see the trailer for love on the beat
571
+ list movie times at megaplex theatres
572
+ will it be chillier at 06:05:48 in wagener réunion
573
+ what is the weather in south bradenton
574
+ get jump down painting
575
+ please book a room in spaghetti warehouse for catalina delores and brandie mendoza at 12 am
576
+ what is the nh forecast for mexican hat
577
+ i need to book a top-rated steakhouse this autumn for 1 around azerbaijan
578
+ will it be chillier at my current location in one minute
579
+ show me heavenly sword
580
+ what is the weather forecast for close-by gu 3 years from now
581
+ will it be freezing on 4/20/2038 in american beach nc
582
+ i need the wather for next week in the philippines
583
+ add tune to my metal crash course playlist
584
+ i would like to book the best food court with persian food within the same area as ok for my ex husband and i
585
+ i d like to see the picture the principle of hope
586
+ rate this series 2 out of 6
587
+ find a man needs a maid
588
+ book a restaurant close by my daughters s work location with burrito three years from now
589
+ add this tune to the refugee playlist
590
+ find time for movie times now
591
+ i would like to book a highly rated brasserie with souvlaki neighboring la next week
592
+ find the panic in needle park
593
+ is it freezing on jun the 21st in apshawa south africa
594
+ i need to take three people to eat
595
+ play a 2006 chant
596
+ show me the schedule of the loves of letty in cinema closest
597
+ play the top 20 ep from the fifties by john bundrick
598
+ show creativity of photograph of my wonderful day
599
+ book a table in the united states for 10 at the berghoff
600
+ i d like to book a brasserie in virginia city ga
601
+ will it be temperate in the same area in vi
602
+ rate the current novel four out of 6 points
603
+ is it going to get chillier near hocking state forest
604
+ for the current saga i rate 2 of 6 stars
605
+ i want to play the video game espn major league soccer
606
+ rate the current book a three
607
+ rate this novel 0 of 6 stars
608
+ is it going to be chillier at 10 pm in texas
609
+ what s the weather in timbo
610
+ add the blurred crusade to crate diggers anonymous
611
+ tell me the weather forecast for sugarloaf provincial park ten weeks from now
612
+ add a gackt camui track to the white noise playlist
613
+ rate canto for a gypsy two of 6 stars
614
+ i m looking for circus world
615
+ this textbook gets a two
616
+ show me the movie times
617
+ add song to my underground hits
618
+ play the album journeyman
619
+ find the family jams saga
620
+ play rob mills album the golden archipelago
621
+ book a spot at a restaurant within walking distance of palau
622
+ find me the balance and timing book
623
+ find movie schedules for bow tie cinemas
624
+ add get happy to cherry s las canciones más lindas del mundo
625
+ rate this textbook a 1
626
+ shw the picture twin husbands
627
+ rate a taste of blackberries a three
628
+ play the 1991 soundtrack from ian mcdonald
629
+ find an album called just call me stupid
630
+ play the insoc ep
631
+ i want to hear major harris s songs from the fifties
632
+ book a restaurant in donnelly
633
+ rate the saint in trouble 1 of 6
634
+ play punk rock music
635
+ look for a photograph of i wanna sex you up
636
+ what is the humidity like in faraway on ak
637
+ i d like to eat at an internet restaurant with a party of four
638
+ when is just before nightfall playing
639
+ play moondog s chupacabra
640
+ add album to pop rising
641
+ rate this book three points
642
+ i am giving this current book album 0 out of 6 stars
643
+ play artist vlada divljan from something he did that is good
644
+ what will the humidity be in varnado georgia at one am
645
+ add no prejudice to 90s indie
646
+ what are the movies movie times nearby
647
+ i want to hear some songs from the twenties
648
+ please make reservations for nine at 3 am
649
+ can you pull up queen of the organ
650
+ lets hear some dawood sarkhosh from their the power of your love album from groove shark
651
+ will it get overcast in la dolores
652
+ book a spot for kelli jean and i at a pub at elevenses
653
+ add this candi staton artist to my dancefloor hits
654
+ i want to add a song by jazz brasileiro
655
+ rate wielding a red sword 0 stars
656
+ book a taverna that serves bengali for six at five
657
+ play the tv series heart of gold
658
+ show crafty hands saga
659
+ will it be hotter in wyomissing hills
660
+ show weather while sunset in the same area in south carolina
661
+ table for one somewhere in palco
662
+ i would like to add something by kuk harrell to my hip hop 2017 new school playlist
663
+ add list of rush instrumentals to this is lady antebellum
664
+ where can i see a slice of life
665
+ the current textbook gets a 2 rating
666
+ add wing track to all a cappella
667
+ show me dangers of the canadian mounted
668
+ please add this this tune to the playlist this is selena
669
+ what will the weather be in stelvio national park 1 hour and 1 minute from now
670
+ can you put musiri subramania iyer s song onto the lo-fi love soundtrack
671
+ i want to add michelle heaton to this is chopin
672
+ show me the movie operetta for the theatre organ
673
+ where s the nearest movie house playing no trains no planes
674
+ put a xiang xiang track onto women of the blues
675
+ can you add a track by david wolfenberger to janell s all funked up playlist
676
+ play the album vibrations by marion elise raven
677
+ add fabri fibra to evening acoustic
678
+ can you play any chant from the fourties
679
+ show the night riders
680
+ i m looking for a movie called salvage mice
681
+ find your personal touch
682
+ add this tune to my weekend playlist
683
+ is it going to storm in black rock alaska
684
+ show the movie schedules at united paramount theatres
685
+ i want to read the saga michael clayton
686
+ book me a table for 3 at tkk fried chicken in sri lanka
687
+ rate this book titled the improvisatore five stars
688
+ book a restaurant for one person at 7 am
689
+ weather for beauregard il
690
+ will there be alot of wind on march 13th in lost creek bahrain
691
+ i d like a reservation at a place in iran for neva alice and maggie parker
692
+ show me movie schedule for animated movie around here at eleven a m
693
+ i give this book dictionary of the english language a 4 rating
694
+ play some symphonic rock
695
+ add to my playlist all funked up this track
696
+ find a tv series called armageddon summer
697
+ find politicsnation with al sharpton
698
+ rate this album 0 points out of 6
699
+ add leah kauffman to my uncharted 4 nathan drake playlist
700
+ rate this album two out of 6
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+ O O B-condition_description O O O O B-current_location I-current_location O B-timeRange O
17
+ O O B-object_name I-object_name I-object_name B-object_type
18
+ O O O O O B-state I-state
19
+ O B-object_location_type I-object_location_type O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
20
+ B-restaurant_type O B-country B-timeRange I-timeRange O O B-party_size_number O
21
+ O O B-object_select B-object_type B-rating_value O B-best_rating B-rating_unit
22
+ O O B-music_item B-playlist I-playlist I-playlist I-playlist I-playlist O B-playlist_owner O
23
+ O O B-music_item O B-artist I-artist O B-playlist I-playlist O
24
+ O O B-object_type I-object_type
25
+ O O B-condition_description O B-city
26
+ O O O O O O B-timeRange I-timeRange O B-state
27
+ B-timeRange I-timeRange I-timeRange O B-movie_name I-movie_name I-movie_name
28
+ O O O O B-party_size_number O O B-sort B-cuisine B-restaurant_type B-spatial_relation I-spatial_relation O B-city
29
+ O O O B-artist I-artist O O O B-year
30
+ O O O B-playlist B-entity_name
31
+ O O B-music_item O B-playlist I-playlist I-playlist
32
+ O O B-object_name I-object_name I-object_name O B-rating_value B-rating_unit
33
+ O O B-year O
34
+ O B-movie_type O O B-spatial_relation
35
+ O B-entity_name I-entity_name O B-playlist I-playlist I-playlist I-playlist I-playlist O
36
+ O O B-object_type I-object_type O B-object_name I-object_name I-object_name
37
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value O B-best_rating B-rating_unit
38
+ O O B-object_type I-object_type
39
+ O O O O O O B-city I-city O B-timeRange I-timeRange I-timeRange
40
+ O B-timeRange I-timeRange O B-country
41
+ O O B-sort B-music_item O B-artist I-artist I-artist O B-service
42
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value O O B-best_rating
43
+ O B-artist O O O B-year
44
+ O O O O O B-city I-city B-state
45
+ O O B-music_item O B-artist I-artist
46
+ O O O O O O O O O B-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi O B-timeRange I-timeRange I-timeRange I-timeRange
47
+ O O O B-artist I-artist
48
+ O O B-object_part_of_series_type B-object_name I-object_name I-object_name O B-rating_value
49
+ O O O O B-party_size_number O O B-restaurant_type O B-city
50
+ O O B-restaurant_type O B-country O B-party_size_number O
51
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
52
+ O O O O O B-restaurant_type O O B-served_dish O B-city O O O O B-party_size_number
53
+ O O B-object_name I-object_name I-object_name B-object_type I-object_type O O
54
+ O O B-restaurant_type O B-cuisine O B-timeRange I-timeRange I-timeRange
55
+ O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value
56
+ O O O O B-party_size_number O O B-restaurant_type O O B-served_dish I-served_dish
57
+ O O B-object_select B-object_type B-rating_value B-rating_unit
58
+ O O B-object_name I-object_name O O B-rating_value
59
+ O B-movie_name I-movie_name O B-location_name I-location_name
60
+ O O O B-object_name I-object_name I-object_name
61
+ O O O O O O B-city B-state O B-timeRange I-timeRange I-timeRange
62
+ O O B-condition_temperature O B-city
63
+ O O O B-music_item O B-playlist_owner O O B-playlist I-playlist I-playlist
64
+ O O B-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
65
+ O O O B-entity_name O B-playlist_owner O O B-playlist
66
+ O O B-object_type O B-spatial_relation B-movie_type I-movie_type
67
+ O O O B-timeRange O O B-restaurant_type O B-party_size_number O O B-served_dish
68
+ O O B-sort B-music_item I-music_item O B-artist O O B-year
69
+ O O B-music_item O B-playlist I-playlist
70
+ B-restaurant_name I-restaurant_name I-restaurant_name B-restaurant_type O B-timeRange I-timeRange O B-party_size_description I-party_size_description I-party_size_description I-party_size_description
71
+ O B-entity_name O B-playlist I-playlist
72
+ O O B-artist I-artist B-music_item O
73
+ O B-rating_value O O B-best_rating B-rating_unit O B-object_select B-object_type
74
+ O O B-object_type I-object_type O B-movie_type I-movie_type B-spatial_relation I-spatial_relation
75
+ O O O B-sort O O B-artist I-artist I-artist
76
+ O B-music_item O B-playlist_owner B-playlist I-playlist O
77
+ O B-entity_name I-entity_name I-entity_name I-entity_name O B-playlist I-playlist
78
+ O B-object_select B-object_type O B-rating_value
79
+ O O O O O B-music_item O O B-year
80
+ O O O B-sort B-music_item O B-artist I-artist O B-service I-service
81
+ O O B-object_type I-object_type O B-object_name I-object_name
82
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value
83
+ O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist
84
+ O O O O O O O B-current_location I-current_location
85
+ O B-entity_name O O B-playlist I-playlist O
86
+ O O O O B-object_name I-object_name
87
+ O O O B-condition_temperature O O B-current_location I-current_location
88
+ O O B-artist I-artist B-music_item O O B-playlist I-playlist I-playlist I-playlist O
89
+ O O B-music_item O O B-playlist I-playlist O
90
+ O B-movie_name I-movie_name I-movie_name
91
+ O B-playlist O O O B-artist I-artist
92
+ O O B-genre O O B-service
93
+ O B-rating_value O O B-object_select B-object_type
94
+ O B-entity_name I-entity_name O B-playlist_owner B-playlist I-playlist O
95
+ O O O O B-entity_name I-entity_name I-entity_name O O O O B-playlist I-playlist I-playlist
96
+ O O O B-movie_name I-movie_name I-movie_name O O O B-location_name I-location_name
97
+ O O B-object_select B-object_part_of_series_type O B-rating_value
98
+ O B-artist I-artist B-music_item O B-playlist_owner B-playlist I-playlist
99
+ O O B-music_item B-artist I-artist I-artist O B-playlist I-playlist
100
+ O O O B-object_name I-object_name I-object_name
101
+ O B-track I-track I-track O B-artist I-artist
102
+ O B-track I-track I-track I-track O B-service
103
+ O O O O B-movie_name I-movie_name O
104
+ O B-entity_name I-entity_name O B-playlist_owner B-playlist I-playlist I-playlist I-playlist O
105
+ O O O B-movie_name I-movie_name O O
106
+ B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name O O O O O B-best_rating O O O O B-rating_value
107
+ O B-playlist_owner B-playlist O O B-entity_name I-entity_name I-entity_name I-entity_name I-entity_name
108
+ O O B-artist I-artist
109
+ O O B-music_item O B-playlist
110
+ O O O B-movie_name I-movie_name I-movie_name O
111
+ O O O B-service
112
+ O O O B-artist I-artist B-music_item O B-playlist_owner B-playlist I-playlist I-playlist I-playlist O
113
+ O O O B-condition_description O B-timeRange I-timeRange O B-city I-city B-state
114
+ O O O B-object_type I-object_type B-object_name I-object_name I-object_name I-object_name
115
+ O O O O O O B-condition_temperature O B-city B-country I-country
116
+ O O B-condition_description O B-city
117
+ O O B-object_type I-object_type O B-object_name I-object_name I-object_name I-object_name
118
+ O O B-object_type I-object_type O B-object_name I-object_name I-object_name
119
+ O O B-music_item B-track I-track I-track O O O B-artist I-artist
120
+ O B-artist O O B-playlist I-playlist O
121
+ O O O O B-restaurant_name I-restaurant_name
122
+ O O O O O B-current_location I-current_location O O O B-timeRange I-timeRange I-timeRange
123
+ O O O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
124
+ O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit O O O O O B-best_rating
125
+ O O O O O B-object_select B-object_part_of_series_type O B-rating_value O O B-best_rating B-rating_unit
126
+ O B-artist I-artist O B-playlist I-playlist I-playlist
127
+ O O B-restaurant_type O O B-served_dish I-served_dish B-spatial_relation B-poi I-poi O B-party_size_number O
128
+ O B-condition_description O B-spatial_relation O B-country
129
+ O O B-restaurant_type O B-party_size_number O O B-timeRange O O B-country I-country I-country I-country I-country
130
+ O O B-object_type O B-movie_type O B-timeRange O B-location_name I-location_name I-location_name
131
+ O O B-condition_description O O B-state I-state I-state
132
+ O O B-object_type I-object_type
133
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value O O B-best_rating
134
+ O O O O O B-city
135
+ O O O B-music_item O B-year
136
+ O O B-object_name I-object_name I-object_name I-object_name
137
+ O O B-object_select B-object_type B-rating_value B-rating_unit O O B-best_rating
138
+ O O B-movie_name I-movie_name I-movie_name O
139
+ O O B-music_item O B-playlist I-playlist I-playlist I-playlist I-playlist
140
+ O B-artist I-artist
141
+ O O O O O B-timeRange I-timeRange I-timeRange O B-city I-city O B-condition_temperature O
142
+ O O O O O B-restaurant_type I-restaurant_type O O O O O B-party_size_number O B-state
143
+ O O O B-service O B-artist I-artist
144
+ O B-entity_name I-entity_name O B-playlist_owner B-playlist O
145
+ O O B-object_type I-object_type B-object_name I-object_name I-object_name
146
+ O B-artist I-artist O B-playlist_owner I-playlist_owner B-playlist I-playlist
147
+ O O O O O O O O O B-city
148
+ O O O O O B-city B-state
149
+ O O B-movie_name I-movie_name I-movie_name B-location_name I-location_name
150
+ O O O O O O B-country I-country I-country I-country O B-timeRange I-timeRange I-timeRange
151
+ O B-movie_type I-movie_type O O B-spatial_relation I-spatial_relation I-spatial_relation
152
+ O O O O O O B-timeRange I-timeRange I-timeRange B-current_location
153
+ O O B-music_item B-track I-track I-track I-track
154
+ O B-artist I-artist B-music_item O
155
+ O O O O B-music_item O B-playlist_owner B-playlist I-playlist I-playlist O
156
+ O B-timeRange O O O O B-current_location O O O B-condition_temperature
157
+ O O O O O B-object_name I-object_name B-object_type
158
+ O B-entity_name I-entity_name I-entity_name I-entity_name I-entity_name O O B-playlist I-playlist O
159
+ O O B-artist I-artist O O B-year
160
+ O O O B-spatial_relation B-poi I-poi I-poi I-poi O O B-sort I-sort O O B-cuisine I-cuisine B-restaurant_type
161
+ O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O
162
+ O O B-condition_description O B-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi
163
+ O B-object_select B-object_type O B-rating_value
164
+ O O O O O O B-restaurant_type B-spatial_relation B-city O B-party_size_number O O O B-served_dish O B-timeRange
165
+ O O B-sort I-sort O O B-state B-timeRange I-timeRange I-timeRange O O B-restaurant_type
166
+ O O O B-location_name I-location_name O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
167
+ O O B-music_item O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist I-playlist I-playlist I-playlist O
168
+ O O B-object_type O B-object_name I-object_name
169
+ O O O O B-party_size_number O B-timeRange O B-state
170
+ O O O O B-object_type I-object_type
171
+ O O B-restaurant_type O B-party_size_number O B-timeRange I-timeRange
172
+ O O O O O O B-movie_type O O O B-object_type I-object_type B-spatial_relation
173
+ O O O O O O B-party_size_number O O B-city B-state
174
+ O O B-object_type I-object_type O B-location_name I-location_name
175
+ O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
176
+ O O B-sort B-music_item O O B-year
177
+ O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist O
178
+ O O B-condition_temperature O B-state
179
+ B-object_name I-object_name I-object_name O O O O B-rating_value O O B-best_rating B-rating_unit O O
180
+ O O O B-condition_description O B-state
181
+ O B-playlist I-playlist I-playlist
182
+ O O B-music_item O O B-year
183
+ O O O O O O B-state O B-timeRange I-timeRange I-timeRange
184
+ O O O B-entity_name O B-playlist I-playlist I-playlist
185
+ O O O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
186
+ O O O O B-object_name
187
+ O B-entity_name I-entity_name I-entity_name I-entity_name I-entity_name O B-playlist_owner B-playlist I-playlist O
188
+ O O B-music_item O B-playlist I-playlist I-playlist
189
+ O O O O O O O B-restaurant_type B-spatial_relation B-country O O O O B-party_size_number O O O B-cuisine
190
+ B-playlist I-playlist I-playlist I-playlist O O O B-artist I-artist I-artist O O
191
+ O O B-object_select B-object_part_of_series_type B-rating_value B-rating_unit
192
+ O B-object_select B-object_type B-rating_value O B-best_rating
193
+ O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value O O B-best_rating B-rating_unit
194
+ O O O O O O B-timeRange O B-restaurant_name I-restaurant_name I-restaurant_name
195
+ O O O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
196
+ O O B-service O B-artist I-artist B-music_item
197
+ O O O B-object_type I-object_type
198
+ O O O O O B-party_size_description I-party_size_description I-party_size_description I-party_size_description O B-country O O B-spatial_relation B-restaurant_type
199
+ O O B-sort I-sort B-music_item O B-artist I-artist O B-service I-service
200
+ O O O B-object_name B-object_type
201
+ O O B-artist I-artist B-music_item O O B-playlist I-playlist O
202
+ O O O B-condition_temperature O B-timeRange I-timeRange I-timeRange O B-state O B-spatial_relation
203
+ O O O O O B-object_type I-object_type O B-object_name I-object_name I-object_name
204
+ O O O O O O O O O B-restaurant_type O O B-served_dish B-spatial_relation I-spatial_relation I-spatial_relation I-spatial_relation O B-country I-country
205
+ O O O O O O B-city
206
+ O O B-music_item O B-playlist_owner B-playlist I-playlist O
207
+ O B-object_select B-object_type B-rating_value O O B-best_rating
208
+ O O O B-object_name
209
+ O O B-object_type O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O O B-spatial_relation B-object_location_type I-object_location_type
210
+ O O O O O O B-city I-city B-country O B-timeRange I-timeRange I-timeRange
211
+ O O O O O O B-state
212
+ O O B-sort B-music_item O B-year
213
+ O B-artist I-artist O O O B-service
214
+ O O O O B-object_type B-object_name I-object_name I-object_name I-object_name
215
+ O O O O O B-country O B-timeRange O
216
+ O B-artist I-artist B-music_item O B-playlist I-playlist I-playlist I-playlist O
217
+ O B-object_name I-object_name I-object_name I-object_name
218
+ O B-music_item B-artist I-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist O
219
+ O O O O O O B-object_name
220
+ O O O O O B-city I-city
221
+ O O B-year O
222
+ O O B-object_type I-object_type O B-object_name I-object_name
223
+ O B-service O O B-artist I-artist B-track I-track I-track I-track I-track
224
+ O O O O O B-object_type I-object_type O B-location_name I-location_name
225
+ O O B-entity_name I-entity_name I-entity_name I-entity_name O O B-playlist_owner B-playlist I-playlist I-playlist O
226
+ O O B-sort B-music_item O B-artist I-artist O B-service I-service
227
+ O O O B-object_type I-object_type O B-object_name I-object_name
228
+ O O B-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name O B-city B-state O B-timeRange I-timeRange I-timeRange
229
+ O O B-object_type O B-object_name I-object_name I-object_name I-object_name
230
+ O B-artist I-artist I-artist O B-music_item O O O B-playlist_owner B-playlist I-playlist O
231
+ O B-movie_type I-movie_type O B-spatial_relation B-object_location_type I-object_location_type
232
+ O O B-object_type B-object_name I-object_name I-object_name
233
+ O O O O B-movie_name I-movie_name I-movie_name O O O B-timeRange I-timeRange I-timeRange I-timeRange
234
+ O O O O B-timeRange O B-country I-country I-country I-country I-country O O B-restaurant_type
235
+ O O O O B-artist I-artist O B-sort I-sort
236
+ O B-movie_type O O O B-spatial_relation B-object_location_type
237
+ O O O O O O B-city I-city I-city O B-country
238
+ O O O O O B-object_name O O B-object_type O
239
+ O O B-playlist_owner B-playlist I-playlist I-playlist O O B-artist I-artist
240
+ B-restaurant_type I-restaurant_type O B-country O B-party_size_number
241
+ O O O B-object_type I-object_type
242
+ O O O O B-party_size_description I-party_size_description I-party_size_description I-party_size_description O B-restaurant_name I-restaurant_name I-restaurant_name O B-country I-country
243
+ O B-object_name I-object_name I-object_name I-object_name
244
+ O O B-object_type I-object_type O B-movie_type B-spatial_relation I-spatial_relation I-spatial_relation
245
+ O O O O O O B-movie_name O B-object_location_type I-object_location_type O B-timeRange I-timeRange
246
+ O B-album I-album I-album I-album O B-artist I-artist
247
+ O O O O O O B-city B-state
248
+ O O B-genre O
249
+ O O B-object_select B-object_type B-rating_value O O B-best_rating
250
+ O B-object_select B-object_type B-rating_value B-rating_unit
251
+ O O O O O B-timeRange O O B-current_location I-current_location
252
+ O B-year O O B-artist I-artist I-artist
253
+ O O O O O B-spatial_relation I-spatial_relation B-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi O B-timeRange O
254
+ O O O B-artist I-artist B-music_item O
255
+ O B-track I-track O B-artist I-artist
256
+ O O B-object_type O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O O B-spatial_relation B-object_location_type B-timeRange I-timeRange I-timeRange
257
+ O O B-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
258
+ O O O O O B-object_select B-object_type B-rating_value O O B-best_rating B-rating_unit
259
+ O O B-object_type I-object_type O B-movie_type I-movie_type O B-timeRange I-timeRange I-timeRange I-timeRange B-spatial_relation I-spatial_relation I-spatial_relation
260
+ O O B-object_type B-object_name I-object_name I-object_name I-object_name
261
+ O O B-music_item O O B-playlist I-playlist O
262
+ O O O B-spatial_relation B-object_location_type I-object_location_type O B-movie_name I-movie_name I-movie_name O B-timeRange I-timeRange
263
+ O O O O O B-country O B-timeRange
264
+ O O O B-entity_name I-entity_name I-entity_name I-entity_name O O O O B-playlist I-playlist
265
+ O B-timeRange I-timeRange I-timeRange O O O O O O B-state O O O B-spatial_relation I-spatial_relation O O
266
+ O O O O O B-country B-timeRange I-timeRange I-timeRange O O O B-condition_temperature
267
+ O O B-music_item O B-artist I-artist O B-playlist I-playlist
268
+ O O B-music_item O B-artist I-artist
269
+ O B-music_item O B-playlist
270
+ O O O O O O O O B-country
271
+ O O O B-service
272
+ O B-entity_name I-entity_name I-entity_name O B-playlist_owner B-playlist I-playlist I-playlist O
273
+ O O O O O B-timeRange I-timeRange I-timeRange I-timeRange O O B-restaurant_type O B-party_size_number B-spatial_relation B-state O O O B-served_dish I-served_dish I-served_dish
274
+ O O O O O B-restaurant_type I-restaurant_type O B-state
275
+ B-timeRange I-timeRange I-timeRange I-timeRange B-party_size_description I-party_size_description I-party_size_description I-party_size_description I-party_size_description O O O B-cuisine O O O B-restaurant_type O B-spatial_relation B-state
276
+ O O B-object_type I-object_type O B-object_name
277
+ O B-movie_type I-movie_type B-spatial_relation I-spatial_relation O O B-object_type I-object_type
278
+ O O O O B-party_size_number O O B-facility B-restaurant_type I-restaurant_type O B-country
279
+ O O O B-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit O O O O O B-best_rating
280
+ O O O O O B-timeRange I-timeRange I-timeRange O O B-restaurant_type O O B-served_dish
281
+ O B-object_name I-object_name I-object_name I-object_name I-object_name
282
+ O O O O O B-party_size_number O O B-restaurant_type O B-state I-state
283
+ O O O B-movie_name I-movie_name I-movie_name O
284
+ O O O O B-condition_description O B-city I-city B-country
285
+ O O B-sort B-music_item O O B-artist
286
+ O O B-movie_type I-movie_type O O B-location_name I-location_name I-location_name
287
+ O O B-object_select B-object_type O B-rating_value
288
+ O O O O B-entity_name I-entity_name O B-playlist_owner O O B-playlist
289
+ O B-object_select B-object_type O B-rating_value B-rating_unit
290
+ O O O O O O B-city I-city B-state O B-timeRange I-timeRange
291
+ O O O O O B-object_type O B-object_name I-object_name
292
+ O O O B-artist I-artist O B-playlist_owner B-playlist I-playlist O
293
+ O B-music_item O B-playlist_owner O B-playlist I-playlist
294
+ O B-movie_type O O O B-spatial_relation I-spatial_relation I-spatial_relation
295
+ O O O B-movie_type O O O B-location_name I-location_name
296
+ O B-entity_name I-entity_name I-entity_name I-entity_name I-entity_name I-entity_name O O B-playlist I-playlist O
297
+ O B-object_type I-object_type
298
+ O O B-object_type B-object_name I-object_name I-object_name I-object_name O B-rating_value
299
+ O B-artist I-artist O B-album I-album I-album I-album
300
+ O O B-music_item O O B-playlist I-playlist I-playlist O
301
+ O O O O B-music_item O B-artist I-artist O B-playlist_owner O O B-playlist I-playlist I-playlist
302
+ O B-object_type I-object_type
303
+ O O B-object_type I-object_type O O
304
+ O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist O
305
+ O O O B-condition_temperature B-current_location B-timeRange I-timeRange I-timeRange
306
+ O O B-country
307
+ O O O O B-object_name I-object_name I-object_name O B-rating_value
308
+ O O O O O B-object_type B-object_name I-object_name
309
+ O B-state O O O B-condition_temperature O B-timeRange I-timeRange
310
+ O B-object_name I-object_name I-object_name B-rating_value B-rating_unit
311
+ O O B-object_select B-object_type B-rating_value O B-best_rating B-rating_unit
312
+ O O O O O B-party_size_number O O B-restaurant_type O B-cuisine O O B-state O B-timeRange I-timeRange I-timeRange I-timeRange
313
+ O B-object_name I-object_name I-object_name I-object_name I-object_name O B-object_type
314
+ O O O O B-sort B-music_item O B-year
315
+ O O B-cuisine B-restaurant_type O B-party_size_description I-party_size_description I-party_size_description I-party_size_description
316
+ O O O O O O B-timeRange I-timeRange I-timeRange I-timeRange O B-city
317
+ O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
318
+ O B-playlist I-playlist
319
+ O O O B-city O O B-state
320
+ O B-movie_name I-movie_name
321
+ O O O B-spatial_relation B-object_location_type I-object_location_type O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
322
+ O O O O B-object_type I-object_type O B-location_name I-location_name
323
+ O O O O O B-party_size_number O O B-sort B-restaurant_type B-timeRange I-timeRange I-timeRange I-timeRange O B-city
324
+ O B-artist I-artist O B-service
325
+ O B-object_name I-object_name I-object_name I-object_name O B-object_type
326
+ O O B-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
327
+ O O B-party_size_number O O B-sort B-restaurant_type I-restaurant_type
328
+ O O O O O B-party_size_number O O O B-spatial_relation B-state B-restaurant_type B-timeRange I-timeRange I-timeRange I-timeRange
329
+ O O B-condition_description B-timeRange O B-state
330
+ O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
331
+ O B-object_type I-object_type
332
+ O B-object_type I-object_type O B-location_name I-location_name I-location_name
333
+ O O O O O B-state O B-timeRange
334
+ O O O B-music_item O B-playlist_owner B-playlist I-playlist O
335
+ O O O B-restaurant_type O
336
+ O B-object_name I-object_name I-object_name I-object_name O B-object_type
337
+ O B-album I-album I-album I-album O B-artist I-artist
338
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
339
+ O B-object_type I-object_type O B-movie_type O B-spatial_relation I-spatial_relation
340
+ O O O O O B-object_type I-object_type O O B-object_name I-object_name I-object_name I-object_name I-object_name
341
+ O B-artist I-artist O B-playlist_owner B-playlist I-playlist O
342
+ O O B-artist I-artist O O O B-year
343
+ O O B-music_item O B-playlist_owner B-playlist I-playlist O
344
+ O B-music_item O B-playlist I-playlist I-playlist O
345
+ O O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name B-timeRange I-timeRange I-timeRange
346
+ O B-rating_value O O B-best_rating B-rating_unit O O B-object_select B-object_type
347
+ O O O O O O B-restaurant_type O B-party_size_number O B-timeRange I-timeRange I-timeRange I-timeRange O B-city
348
+ O O B-service I-service O O O B-year B-music_item O B-artist
349
+ O O O B-spatial_relation B-object_location_type O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
350
+ O O O O O O O B-object_type O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
351
+ O B-movie_type O B-spatial_relation I-spatial_relation
352
+ O O B-restaurant_type B-spatial_relation O B-poi
353
+ O B-object_name I-object_name I-object_name O B-object_type
354
+ O O B-track I-track I-track
355
+ O O B-object_type I-object_type O B-object_name
356
+ O B-movie_name I-movie_name I-movie_name I-movie_name O O B-location_name I-location_name I-location_name
357
+ O O B-object_select B-object_type B-rating_value B-rating_unit
358
+ O O B-timeRange I-timeRange B-current_location
359
+ O B-movie_type I-movie_type O O O O B-spatial_relation B-object_location_type I-object_location_type
360
+ O B-object_select B-object_type B-rating_value O B-best_rating B-rating_unit
361
+ O O O O O B-movie_name I-movie_name I-movie_name I-movie_name
362
+ B-object_name O O O O O O O B-rating_value O O B-best_rating
363
+ O O O B-object_type O B-movie_type B-spatial_relation I-spatial_relation I-spatial_relation
364
+ O O O O B-party_size_number O O B-country I-country I-country I-country
365
+ O O O B-object_name I-object_name I-object_name I-object_name O O O O B-best_rating O O O O B-rating_value
366
+ O B-movie_type I-movie_type O O B-spatial_relation
367
+ O O O O B-condition_description B-current_location O B-timeRange
368
+ O O O O O B-object_part_of_series_type B-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
369
+ O O O O O O O O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O B-location_name I-location_name
370
+ O B-album I-album I-album I-album O B-artist I-artist
371
+ O O O O B-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name B-spatial_relation O B-poi
372
+ O B-artist O B-playlist_owner B-playlist I-playlist I-playlist O
373
+ O O O B-object_name I-object_name I-object_name B-object_type
374
+ O O B-restaurant_type O B-state O O B-served_dish
375
+ O O O O B-object_select B-object_type B-rating_value B-rating_unit O O O O O B-best_rating
376
+ O O O O O B-cuisine B-restaurant_type O B-state O B-party_size_description I-party_size_description I-party_size_description I-party_size_description I-party_size_description
377
+ O B-condition_description O O O O O B-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi
378
+ O B-music_item O B-playlist I-playlist O
379
+ O O O O O B-sort B-cuisine B-restaurant_type O B-spatial_relation O O O B-timeRange
380
+ O O O O O B-party_size_number
381
+ O O B-music_item O B-playlist_owner B-playlist O
382
+ O B-object_select B-object_type O B-rating_value
383
+ O O O O O O B-timeRange I-timeRange O O O B-spatial_relation B-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi
384
+ O O O O O B-city O B-timeRange I-timeRange I-timeRange O B-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name
385
+ O O O O O B-party_size_number O B-restaurant_name I-restaurant_name O B-country
386
+ O O O O O B-object_type B-object_name I-object_name I-object_name
387
+ O O O O O O O O B-party_size_number O B-timeRange
388
+ O O O O O O B-party_size_number O B-timeRange I-timeRange I-timeRange O O O O B-state
389
+ O O O B-restaurant_type O B-party_size_number O B-city
390
+ O O O O O O B-party_size_number B-timeRange I-timeRange I-timeRange O B-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name
391
+ O O B-object_location_type I-object_location_type O B-timeRange O B-movie_name I-movie_name I-movie_name I-movie_name
392
+ O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type I-object_type
393
+ O O O O B-spatial_relation O B-city B-timeRange I-timeRange I-timeRange I-timeRange
394
+ O B-playlist_owner O B-playlist O O O B-entity_name I-entity_name I-entity_name
395
+ O O O B-object_name I-object_name B-object_type I-object_type
396
+ O B-object_type I-object_type
397
+ O B-playlist O
398
+ O O O B-movie_type I-movie_type O O O O O B-spatial_relation B-object_location_type I-object_location_type
399
+ O O O O O O B-object_type B-object_name I-object_name
400
+ O O O B-movie_name I-movie_name O O O B-object_location_type I-object_location_type
401
+ O O B-object_type B-object_name I-object_name
402
+ O O O O O B-condition_temperature O B-geographic_poi I-geographic_poi I-geographic_poi I-geographic_poi
403
+ O O B-music_item O B-playlist_owner I-playlist_owner B-playlist I-playlist O
404
+ O O B-music_item O B-artist I-artist I-artist
405
+ O O B-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value O B-best_rating
406
+ O O O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name I-movie_name O O O B-object_location_type I-object_location_type
407
+ O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist O
408
+ O O O O O B-movie_name I-movie_name I-movie_name
409
+ O O O B-location_name I-location_name O O B-movie_name I-movie_name
410
+ O O O B-condition_description O B-geographic_poi I-geographic_poi I-geographic_poi
411
+ O B-artist I-artist O O B-service O O B-sort
412
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value O B-best_rating
413
+ O O O B-object_type I-object_type B-object_name I-object_name I-object_name
414
+ O O O O O B-object_type I-object_type O B-object_name
415
+ O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
416
+ O O B-object_name I-object_name I-object_name B-rating_value B-rating_unit O O B-best_rating
417
+ O B-playlist I-playlist I-playlist I-playlist I-playlist
418
+ O B-artist O B-playlist_owner B-playlist I-playlist O
419
+ O B-artist I-artist I-artist O B-playlist_owner B-playlist I-playlist O
420
+ O O O B-movie_name I-movie_name I-movie_name O O B-location_name I-location_name
421
+ O B-entity_name O B-playlist_owner B-playlist I-playlist I-playlist I-playlist O
422
+ O B-object_part_of_series_type B-object_name I-object_name O B-rating_value B-rating_unit O O
423
+ O B-object_name I-object_name I-object_name I-object_name
424
+ O O O B-spatial_relation B-object_location_type I-object_location_type O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
425
+ O B-music_item O O B-artist I-artist O B-service O O B-sort
426
+ O O B-music_item B-track I-track I-track
427
+ O O B-sort B-restaurant_type O B-cuisine O
428
+ O B-movie_type I-movie_type O O B-spatial_relation I-spatial_relation I-spatial_relation O O
429
+ O O O O O O B-object_type B-object_name I-object_name I-object_name
430
+ O O O O O O O B-sort B-restaurant_type
431
+ O O O O O B-condition_temperature O B-country I-country O B-timeRange I-timeRange
432
+ O O O O O B-restaurant_type O B-party_size_number B-spatial_relation B-city
433
+ O B-object_name I-object_name I-object_name B-rating_value O B-best_rating B-rating_unit
434
+ O B-object_type B-object_name I-object_name I-object_name O O B-rating_value B-rating_unit O O O
435
+ O O O O O B-restaurant_type O B-city B-state
436
+ O O O O B-object_name I-object_name I-object_name O B-object_type I-object_type
437
+ O O O O O O B-restaurant_type I-restaurant_type O O B-served_dish
438
+ O O B-music_item O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist O
439
+ O O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist O
440
+ O O O O O B-country
441
+ O B-object_select B-object_type O B-rating_value
442
+ O O B-artist I-artist I-artist B-music_item O B-playlist_owner O O B-playlist I-playlist I-playlist
443
+ O O O O B-condition_description B-timeRange I-timeRange O B-state
444
+ O B-movie_name I-movie_name I-movie_name I-movie_name O O O B-spatial_relation B-object_location_type O B-timeRange
445
+ O O O O O O B-movie_type I-movie_type B-spatial_relation I-spatial_relation I-spatial_relation
446
+ O O B-object_type I-object_type B-object_name I-object_name I-object_name
447
+ O O O O O B-poi I-poi I-poi O B-spatial_relation O O O O O B-party_size_number
448
+ O O O O O O B-playlist I-playlist I-playlist O B-playlist_owner O B-music_item
449
+ O O O O O B-restaurant_type O B-party_size_number O B-city
450
+ O O O O B-object_type I-object_type B-object_name I-object_name
451
+ O O B-artist I-artist B-music_item I-music_item O O B-year O B-service
452
+ O O O O O O O B-sort B-restaurant_type O B-country O O O O B-party_size_number
453
+ O O O O O O B-current_location I-current_location O B-timeRange I-timeRange
454
+ O B-object_name I-object_name B-rating_value B-rating_unit O O B-best_rating
455
+ B-timeRange I-timeRange I-timeRange O O O B-condition_description O B-geographic_poi I-geographic_poi I-geographic_poi
456
+ O B-condition_temperature O O O O B-state O B-timeRange I-timeRange
457
+ O O O O O B-entity_name O B-playlist I-playlist I-playlist I-playlist I-playlist I-playlist
458
+ O O O B-condition_temperature O B-city B-state
459
+ O B-artist O B-playlist_owner I-playlist_owner B-playlist I-playlist O
460
+ O O O O O O B-country O B-timeRange I-timeRange
461
+ O B-object_type I-object_type O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
462
+ O B-artist I-artist O B-service O O O B-music_item O O O B-sort
463
+ O O B-artist I-artist O B-playlist_owner O B-playlist I-playlist I-playlist
464
+ O O O O B-state
465
+ O O O B-object_part_of_series_type B-object_name I-object_name I-object_name I-object_name O B-rating_value O B-best_rating B-rating_unit
466
+ O B-entity_name O B-playlist I-playlist
467
+ O O O B-condition_description O O B-city B-country
468
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value O B-best_rating
469
+ O O B-condition_description O B-city
470
+ O O O B-artist I-artist B-music_item
471
+ O O B-object_type I-object_type B-object_name I-object_name I-object_name
472
+ O O O O O B-artist I-artist B-music_item I-music_item
473
+ O O O O O B-condition_description O B-current_location B-timeRange I-timeRange I-timeRange I-timeRange
474
+ O O O O B-restaurant_name I-restaurant_name I-restaurant_name O B-party_size_number O B-timeRange I-timeRange I-timeRange
475
+ O O B-object_type O B-object_name I-object_name I-object_name I-object_name I-object_name
476
+ O B-object_name I-object_name B-rating_value O O B-best_rating
477
+ O O B-music_item O B-playlist_owner B-playlist I-playlist I-playlist I-playlist I-playlist O
478
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
479
+ O O B-year B-music_item I-music_item O B-service
480
+ O O B-state O O B-timeRange
481
+ O O B-music_item O B-artist I-artist
482
+ O O O B-condition_description O B-country
483
+ O O O O O B-timeRange I-timeRange I-timeRange O B-city B-country
484
+ O O O O O O O O B-music_item O B-playlist_owner B-playlist I-playlist O
485
+ O O B-object_name I-object_name B-object_type
486
+ O O O B-object_type I-object_type O B-location_name I-location_name
487
+ O O O B-object_type I-object_type
488
+ O B-entity_name I-entity_name I-entity_name O B-playlist_owner I-playlist_owner B-playlist I-playlist O
489
+ O B-music_item O B-artist I-artist I-artist
490
+ O B-rating_value B-rating_unit O B-object_select B-object_type
491
+ O B-entity_name I-entity_name I-entity_name I-entity_name O B-playlist_owner B-playlist I-playlist O
492
+ O B-entity_name I-entity_name I-entity_name I-entity_name O B-playlist_owner B-playlist I-playlist O
493
+ O O O B-timeRange O O B-state I-state
494
+ O B-entity_name O B-playlist_owner B-playlist I-playlist O
495
+ O O O B-object_type O O O B-object_name
496
+ O B-artist I-artist I-artist O B-playlist I-playlist
497
+ O O O O O B-movie_name I-movie_name I-movie_name O O B-object_location_type I-object_location_type
498
+ O O B-artist I-artist O B-playlist_owner O B-playlist I-playlist I-playlist
499
+ O B-artist I-artist B-music_item O B-playlist I-playlist I-playlist I-playlist I-playlist
500
+ O O B-music_item O B-artist O B-playlist_owner B-playlist I-playlist O
501
+ O O O O B-condition_description B-timeRange O B-city
502
+ O B-object_select B-object_type O B-rating_value O O B-best_rating
503
+ O O B-object_type I-object_type O B-movie_type I-movie_type B-spatial_relation O B-timeRange I-timeRange
504
+ O B-artist I-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist I-playlist O
505
+ O B-object_select B-object_part_of_series_type O B-rating_value
506
+ O O O O O B-restaurant_type O O B-facility O O O O O O B-party_size_number
507
+ O O O B-movie_name I-movie_name O
508
+ O O B-restaurant_name I-restaurant_name O B-city B-state
509
+ O B-movie_type O O B-location_name I-location_name
510
+ O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-rating_value O B-best_rating
511
+ O O O O O B-movie_name I-movie_name
512
+ O O O O B-service
513
+ O O O O B-object_name I-object_name I-object_name B-rating_value O O B-best_rating
514
+ O B-music_item O B-playlist_owner B-playlist I-playlist O
515
+ O O O O O O B-spatial_relation B-country
516
+ O O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
517
+ O O B-object_name I-object_name I-object_name I-object_name
518
+ O B-artist I-artist I-artist O B-playlist_owner B-playlist I-playlist O
519
+ O B-entity_name I-entity_name O B-playlist I-playlist
520
+ O O O O B-poi I-poi B-restaurant_type B-spatial_relation O B-party_size_number B-timeRange I-timeRange I-timeRange I-timeRange
521
+ O O O O O B-object_type O B-object_name I-object_name
522
+ O O B-movie_type O B-location_name I-location_name
523
+ O O B-object_select B-object_part_of_series_type I-object_part_of_series_type B-rating_value O O B-best_rating B-rating_unit
524
+ O O O O B-object_type I-object_type
525
+ O O O O B-entity_name I-entity_name O B-playlist_owner B-playlist I-playlist I-playlist I-playlist I-playlist O
526
+ O O B-genre O B-service
527
+ O O O B-condition_temperature O O B-country I-country I-country
528
+ O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name I-object_name
529
+ O B-rating_value O O B-object_name I-object_name I-object_name
530
+ O O O B-object_type I-object_type B-object_name I-object_name I-object_name I-object_name
531
+ O B-movie_type O O O O B-spatial_relation B-object_location_type
532
+ O O B-music_item O B-artist I-artist O B-playlist_owner I-playlist_owner B-playlist I-playlist I-playlist I-playlist O
533
+ O O O O O B-object_type I-object_type B-object_name I-object_name I-object_name I-object_name
534
+ O O O O O B-party_size_number O O B-sort I-sort B-restaurant_type O B-country
535
+ O O O O B-condition_description O B-city
536
+ O O B-music_item O B-playlist I-playlist I-playlist I-playlist I-playlist I-playlist O
537
+ O O O O B-movie_type O O O B-spatial_relation B-object_location_type I-object_location_type
538
+ O O O O O B-track I-track I-track O B-artist I-artist
539
+ O O O O O O B-city
540
+ O O O O B-city O B-timeRange I-timeRange O O B-sort I-sort B-cuisine B-restaurant_type
541
+ O O O B-year B-music_item I-music_item
542
+ O O O O B-object_name I-object_name I-object_name I-object_name
543
+ O O O O B-artist I-artist O B-music_item O O O B-playlist I-playlist I-playlist O
544
+ O O O O B-object_type I-object_type O B-location_name I-location_name
545
+ O O O O O B-movie_name I-movie_name I-movie_name I-movie_name
546
+ O O O O O B-movie_name I-movie_name
547
+ O O O B-object_type B-object_name I-object_name I-object_name
548
+ O B-movie_name I-movie_name I-movie_name I-movie_name O
549
+ O O O O B-object_type I-object_type
550
+ O B-object_name I-object_name I-object_name B-rating_value
551
+ O O O O O B-music_item O O B-playlist I-playlist I-playlist O
552
+ O O B-music_item O B-playlist_owner B-playlist I-playlist O
553
+ O O B-music_item O B-artist I-artist O B-service
554
+ O O B-condition_description O O B-city I-city
555
+ O B-rating_value B-rating_unit O B-object_name I-object_name I-object_name
556
+ O O B-music_item O B-playlist_owner B-playlist I-playlist O
557
+ O O O O B-object_type I-object_type
558
+ O O O O O B-movie_name
559
+ O B-object_type I-object_type O B-location_name I-location_name
560
+ O B-movie_type O O B-spatial_relation I-spatial_relation I-spatial_relation
561
+ O O O B-playlist O B-service
562
+ O O O O O O O B-timeRange I-timeRange I-timeRange O B-state
563
+ O B-movie_type I-movie_type O O B-spatial_relation I-spatial_relation I-spatial_relation O O
564
+ O O O O B-restaurant_name I-restaurant_name I-restaurant_name I-restaurant_name O O B-spatial_relation B-state
565
+ O O O O O B-object_name I-object_name I-object_name I-object_name I-object_name I-object_name B-object_type
566
+ O B-artist I-artist O B-playlist I-playlist I-playlist I-playlist I-playlist
567
+ O O B-music_item B-album I-album
568
+ O O O O O B-object_name I-object_name I-object_name I-object_name B-object_type I-object_type
569
+ O O B-music_item O B-playlist_owner B-playlist I-playlist I-playlist O
570
+ O O O O O B-object_type O B-object_name I-object_name I-object_name I-object_name
571
+ O B-object_type I-object_type O B-location_name I-location_name
572
+ O O O B-condition_temperature O B-timeRange O B-city B-country
573
+ O O O O O B-city I-city
574
+ O B-object_name I-object_name B-object_type
575
+ O O O O O B-restaurant_name I-restaurant_name O B-party_size_description I-party_size_description I-party_size_description I-party_size_description I-party_size_description O B-timeRange I-timeRange
576
+ O O O B-state O O B-city I-city
577
+ O O O O O B-sort B-restaurant_type B-timeRange I-timeRange O B-party_size_number B-spatial_relation B-country
578
+ O O O B-condition_temperature O O B-current_location I-current_location B-timeRange I-timeRange I-timeRange
579
+ O O B-object_name I-object_name
580
+ O O O O O O B-spatial_relation B-state B-timeRange I-timeRange I-timeRange I-timeRange
581
+ O O O B-condition_temperature O B-timeRange O B-city I-city B-state
582
+ O O O O O B-timeRange I-timeRange O O B-country
583
+ O B-music_item O B-playlist_owner B-playlist I-playlist I-playlist O
584
+ O O O O O O B-sort B-restaurant_type I-restaurant_type O B-cuisine O B-spatial_relation I-spatial_relation I-spatial_relation I-spatial_relation O B-state O B-party_size_description I-party_size_description I-party_size_description I-party_size_description I-party_size_description
585
+ O O O O O O B-object_type B-object_name I-object_name I-object_name I-object_name
586
+ O B-object_select B-object_part_of_series_type B-rating_value O O B-best_rating
587
+ O B-object_name I-object_name I-object_name I-object_name I-object_name
588
+ O O B-restaurant_type B-spatial_relation I-spatial_relation B-poi I-poi I-poi I-poi I-poi O B-served_dish B-timeRange I-timeRange I-timeRange I-timeRange
589
+ O O B-music_item O B-playlist I-playlist I-playlist
590
+ O O O B-object_type I-object_type B-timeRange
591
+ O O O O O O B-sort I-sort B-restaurant_type O B-cuisine B-spatial_relation B-state B-timeRange I-timeRange
592
+ O B-movie_name I-movie_name I-movie_name I-movie_name I-movie_name
593
+ O O B-condition_temperature O B-timeRange I-timeRange I-timeRange O B-city B-country I-country
594
+ O O O O B-party_size_number O O O
595
+ O O B-year B-music_item
596
+ O O O B-object_type O B-movie_name I-movie_name I-movie_name I-movie_name O B-object_location_type B-spatial_relation
597
+ O O B-sort I-sort B-music_item O O B-year O B-artist I-artist
598
+ O O O B-object_type O B-object_name I-object_name I-object_name
599
+ O O O O O B-country I-country O B-party_size_number O B-restaurant_name I-restaurant_name
600
+ O O O O O O B-restaurant_type O B-city I-city B-state
601
+ O O O B-condition_temperature B-spatial_relation I-spatial_relation I-spatial_relation I-spatial_relation O B-state
602
+ O O B-object_select B-object_type B-rating_value O O B-best_rating B-rating_unit
603
+ O O O O O B-condition_temperature B-spatial_relation B-geographic_poi I-geographic_poi I-geographic_poi
604
+ O O B-object_select B-object_part_of_series_type O O B-rating_value O B-best_rating B-rating_unit
605
+ O O O O O B-object_type I-object_type B-object_name I-object_name I-object_name I-object_name
606
+ O O B-object_select B-object_type O B-rating_value
607
+ O B-object_select B-object_type B-rating_value O B-best_rating B-rating_unit
608
+ O O O O O B-condition_temperature O B-timeRange I-timeRange O B-state
609
+ O O O O O B-city
610
+ O B-entity_name I-entity_name I-entity_name O B-playlist I-playlist I-playlist
611
+ O O O O O O B-geographic_poi I-geographic_poi I-geographic_poi B-timeRange I-timeRange I-timeRange I-timeRange
612
+ O O B-artist I-artist B-music_item O O B-playlist I-playlist O
613
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value O B-best_rating B-rating_unit
614
+ O O O O B-object_name I-object_name
615
+ B-object_select B-object_type O O B-rating_value
616
+ O O O B-object_type I-object_type
617
+ O B-music_item O B-playlist_owner B-playlist I-playlist
618
+ O O B-object_type B-object_name
619
+ O B-object_name I-object_name I-object_name B-object_type
620
+ O B-artist I-artist B-music_item B-album I-album I-album
621
+ O O O O O B-restaurant_type B-spatial_relation I-spatial_relation I-spatial_relation O B-state
622
+ O O O B-object_name I-object_name I-object_name B-object_type
623
+ O B-object_type I-object_type O B-location_name I-location_name I-location_name
624
+ O B-entity_name I-entity_name O B-playlist_owner I-playlist_owner B-playlist I-playlist I-playlist I-playlist I-playlist I-playlist
625
+ O B-object_select B-object_type O B-rating_value
626
+ O O B-object_type B-object_name I-object_name
627
+ O B-object_name I-object_name I-object_name I-object_name O B-rating_value
628
+ O O B-year B-music_item O B-artist I-artist
629
+ O O B-object_type O B-object_name I-object_name I-object_name I-object_name
630
+ O B-album I-album I-album
631
+ O O O O B-artist I-artist O O O O B-year
632
+ O O B-restaurant_type O B-city
633
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value O B-best_rating
634
+ O B-genre I-genre O
635
+ O O O B-object_type O B-object_name I-object_name I-object_name I-object_name I-object_name
636
+ O O O B-condition_description O O B-spatial_relation O B-state
637
+ O O O O O O O B-facility B-restaurant_type O O O O B-party_size_number
638
+ O O B-movie_name I-movie_name I-movie_name O
639
+ O B-artist O B-album
640
+ O B-music_item O B-playlist I-playlist
641
+ O B-object_select B-object_type B-rating_value B-rating_unit
642
+ O O O O B-object_select B-object_type I-object_type B-rating_value O O B-best_rating B-rating_unit
643
+ O O B-artist I-artist O O O O O O B-sort
644
+ O O O B-condition_description O O B-city B-state O B-timeRange I-timeRange
645
+ O B-entity_name I-entity_name O B-playlist I-playlist
646
+ O O O B-movie_type B-object_type I-object_type B-spatial_relation
647
+ O O O O O O O O B-year
648
+ O O O O B-party_size_number O B-timeRange I-timeRange
649
+ O O O O B-object_name I-object_name I-object_name I-object_name
650
+ O O O B-artist I-artist O O B-album I-album I-album I-album I-album B-music_item O B-service I-service
651
+ O O O B-condition_description O B-city I-city
652
+ O O O O B-party_size_description I-party_size_description I-party_size_description I-party_size_description O O B-restaurant_type O B-timeRange
653
+ O O B-artist I-artist B-music_item O B-playlist_owner B-playlist I-playlist
654
+ O O O O O B-music_item O B-playlist I-playlist
655
+ O B-object_name I-object_name I-object_name I-object_name B-rating_value B-rating_unit
656
+ O O B-restaurant_type O O B-cuisine O B-party_size_number O B-timeRange
657
+ O O B-object_type I-object_type B-object_name I-object_name I-object_name
658
+ O B-object_name I-object_name B-object_type
659
+ O O O B-condition_temperature O B-city I-city
660
+ O O O B-timeRange B-spatial_relation I-spatial_relation I-spatial_relation I-spatial_relation O B-state I-state
661
+ O O B-party_size_number O O B-city
662
+ O O O O O O O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist I-playlist O
663
+ O B-entity_name I-entity_name I-entity_name I-entity_name O B-playlist I-playlist I-playlist I-playlist
664
+ O O O O B-movie_name I-movie_name I-movie_name I-movie_name
665
+ O B-object_select B-object_type O O B-rating_value O
666
+ O B-artist B-music_item O B-playlist I-playlist I-playlist
667
+ O O B-object_name I-object_name I-object_name I-object_name I-object_name
668
+ O O O O B-music_item O O O B-playlist I-playlist I-playlist
669
+ O O O O O O B-geographic_poi I-geographic_poi I-geographic_poi B-timeRange I-timeRange I-timeRange I-timeRange I-timeRange I-timeRange I-timeRange
670
+ O O O B-artist I-artist I-artist O B-music_item O O B-playlist I-playlist O
671
+ O O O O B-artist I-artist O B-playlist I-playlist I-playlist
672
+ O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name
673
+ O O O B-spatial_relation B-object_location_type I-object_location_type O B-movie_name I-movie_name I-movie_name I-movie_name
674
+ O O B-artist I-artist B-music_item O B-playlist I-playlist I-playlist I-playlist
675
+ O O O O B-music_item O B-artist I-artist O B-playlist_owner I-playlist_owner B-playlist I-playlist I-playlist O
676
+ O O B-music_item B-album O B-artist I-artist I-artist
677
+ O B-artist I-artist O B-playlist I-playlist
678
+ O O O O B-music_item O O B-year
679
+ O B-object_name I-object_name I-object_name
680
+ O O O O O B-object_type O B-object_name I-object_name
681
+ O B-object_name I-object_name I-object_name
682
+ O O B-music_item O B-playlist_owner B-playlist O
683
+ O O O O B-condition_description O B-city I-city B-state
684
+ O O B-object_type I-object_type O B-location_name I-location_name I-location_name
685
+ O O O O O B-object_type B-object_name I-object_name
686
+ O O O O O B-party_size_number O B-restaurant_name I-restaurant_name I-restaurant_name O B-country I-country
687
+ O O B-object_type O B-object_name I-object_name B-rating_value B-rating_unit
688
+ O O B-restaurant_type O B-party_size_number O O B-timeRange I-timeRange
689
+ O O B-city B-state
690
+ O O O O O B-condition_description O B-timeRange I-timeRange O B-city I-city B-country
691
+ O O O O O O O O O B-country O B-party_size_description I-party_size_description I-party_size_description I-party_size_description I-party_size_description
692
+ O O B-object_type I-object_type O B-movie_type I-movie_type B-spatial_relation I-spatial_relation O B-timeRange I-timeRange I-timeRange
693
+ O O O B-object_type B-object_name I-object_name I-object_name I-object_name I-object_name O B-rating_value O
694
+ O O B-genre I-genre
695
+ O O B-playlist_owner O B-playlist I-playlist I-playlist O B-music_item
696
+ O O B-object_type I-object_type O B-object_name I-object_name
697
+ O B-object_name I-object_name I-object_name I-object_name
698
+ O B-object_select B-object_type B-rating_value B-rating_unit O O B-best_rating
699
+ O B-artist I-artist O B-playlist_owner B-playlist I-playlist I-playlist I-playlist O
700
+ O B-object_select B-object_type B-rating_value O O B-best_rating
JointBERT-master/data/snips/train/label ADDED
The diff for this file is too large to render. See raw diff
 
JointBERT-master/data/snips/train/seq.in ADDED
The diff for this file is too large to render. See raw diff
 
JointBERT-master/data/snips/train/seq.out ADDED
The diff for this file is too large to render. See raw diff
 
JointBERT-master/data/vocab_process.py ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import os
2
+
3
+
4
+ def vocab_process(data_dir):
5
+ slot_label_vocab = 'slot_label.txt'
6
+ intent_label_vocab = 'intent_label.txt'
7
+
8
+ train_dir = os.path.join(data_dir, 'train')
9
+ # intent
10
+ with open(os.path.join(train_dir, 'label'), 'r', encoding='utf-8') as f_r, open(os.path.join(data_dir, intent_label_vocab), 'w',
11
+ encoding='utf-8') as f_w:
12
+ intent_vocab = set()
13
+ for line in f_r:
14
+ line = line.strip()
15
+ intent_vocab.add(line)
16
+
17
+ additional_tokens = ["UNK"]
18
+ for token in additional_tokens:
19
+ f_w.write(token + '\n')
20
+
21
+ intent_vocab = sorted(list(intent_vocab))
22
+ for intent in intent_vocab:
23
+ f_w.write(intent + '\n')
24
+
25
+ # slot
26
+ with open(os.path.join(train_dir, 'seq.out'), 'r', encoding='utf-8') as f_r, open(os.path.join(data_dir, slot_label_vocab), 'w',
27
+ encoding='utf-8') as f_w:
28
+ slot_vocab = set()
29
+ for line in f_r:
30
+ line = line.strip()
31
+ slots = line.split()
32
+ for slot in slots:
33
+ slot_vocab.add(slot)
34
+
35
+ slot_vocab = sorted(list(slot_vocab), key=lambda x: (x[2:], x[:2]))
36
+
37
+ # Write additional tokens
38
+ additional_tokens = ["PAD", "UNK"]
39
+ for token in additional_tokens:
40
+ f_w.write(token + '\n')
41
+
42
+ for slot in slot_vocab:
43
+ f_w.write(slot + '\n')
44
+
45
+
46
+ if __name__ == "__main__":
47
+ vocab_process('atis')
48
+ vocab_process('snips')
JointBERT-master/data_loader.py ADDED
@@ -0,0 +1,255 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import os
2
+ import copy
3
+ import json
4
+ import logging
5
+
6
+ import torch
7
+ from torch.utils.data import TensorDataset
8
+
9
+ from utils import get_intent_labels, get_slot_labels
10
+
11
+ logger = logging.getLogger(__name__)
12
+
13
+
14
+ class InputExample(object):
15
+ """
16
+ A single training/test example for simple sequence classification.
17
+
18
+ Args:
19
+ guid: Unique id for the example.
20
+ words: list. The words of the sequence.
21
+ intent_label: (Optional) string. The intent label of the example.
22
+ slot_labels: (Optional) list. The slot labels of the example.
23
+ """
24
+
25
+ def __init__(self, guid, words, intent_label=None, slot_labels=None):
26
+ self.guid = guid
27
+ self.words = words
28
+ self.intent_label = intent_label
29
+ self.slot_labels = slot_labels
30
+
31
+ def __repr__(self):
32
+ return str(self.to_json_string())
33
+
34
+ def to_dict(self):
35
+ """Serializes this instance to a Python dictionary."""
36
+ output = copy.deepcopy(self.__dict__)
37
+ return output
38
+
39
+ def to_json_string(self):
40
+ """Serializes this instance to a JSON string."""
41
+ return json.dumps(self.to_dict(), indent=2, sort_keys=True) + "\n"
42
+
43
+
44
+ class InputFeatures(object):
45
+ """A single set of features of data."""
46
+
47
+ def __init__(self, input_ids, attention_mask, token_type_ids, intent_label_id, slot_labels_ids):
48
+ self.input_ids = input_ids
49
+ self.attention_mask = attention_mask
50
+ self.token_type_ids = token_type_ids
51
+ self.intent_label_id = intent_label_id
52
+ self.slot_labels_ids = slot_labels_ids
53
+
54
+ def __repr__(self):
55
+ return str(self.to_json_string())
56
+
57
+ def to_dict(self):
58
+ """Serializes this instance to a Python dictionary."""
59
+ output = copy.deepcopy(self.__dict__)
60
+ return output
61
+
62
+ def to_json_string(self):
63
+ """Serializes this instance to a JSON string."""
64
+ return json.dumps(self.to_dict(), indent=2, sort_keys=True) + "\n"
65
+
66
+
67
+ class JointProcessor(object):
68
+ """Processor for the JointBERT data set """
69
+
70
+ def __init__(self, args):
71
+ self.args = args
72
+ self.intent_labels = get_intent_labels(args)
73
+ self.slot_labels = get_slot_labels(args)
74
+
75
+ self.input_text_file = 'seq.in'
76
+ self.intent_label_file = 'label'
77
+ self.slot_labels_file = 'seq.out'
78
+
79
+ @classmethod
80
+ def _read_file(cls, input_file, quotechar=None):
81
+ """Reads a tab separated value file."""
82
+ with open(input_file, "r", encoding="utf-8") as f:
83
+ lines = []
84
+ for line in f:
85
+ lines.append(line.strip())
86
+ return lines
87
+
88
+ def _create_examples(self, texts, intents, slots, set_type):
89
+ """Creates examples for the training and dev sets."""
90
+ examples = []
91
+ for i, (text, intent, slot) in enumerate(zip(texts, intents, slots)):
92
+ guid = "%s-%s" % (set_type, i)
93
+ # 1. input_text
94
+ words = text.split() # Some are spaced twice
95
+ # 2. intent
96
+ intent_label = self.intent_labels.index(intent) if intent in self.intent_labels else self.intent_labels.index("UNK")
97
+ # 3. slot
98
+ slot_labels = []
99
+ for s in slot.split():
100
+ slot_labels.append(self.slot_labels.index(s) if s in self.slot_labels else self.slot_labels.index("UNK"))
101
+
102
+ assert len(words) == len(slot_labels)
103
+ examples.append(InputExample(guid=guid, words=words, intent_label=intent_label, slot_labels=slot_labels))
104
+ return examples
105
+
106
+ def get_examples(self, mode):
107
+ """
108
+ Args:
109
+ mode: train, dev, test
110
+ """
111
+ data_path = os.path.join(self.args.data_dir, self.args.task, mode)
112
+ logger.info("LOOKING AT {}".format(data_path))
113
+ return self._create_examples(texts=self._read_file(os.path.join(data_path, self.input_text_file)),
114
+ intents=self._read_file(os.path.join(data_path, self.intent_label_file)),
115
+ slots=self._read_file(os.path.join(data_path, self.slot_labels_file)),
116
+ set_type=mode)
117
+
118
+
119
+ processors = {
120
+ "atis": JointProcessor,
121
+ "snips": JointProcessor
122
+ }
123
+
124
+
125
+ def convert_examples_to_features(examples, max_seq_len, tokenizer,
126
+ pad_token_label_id=-100,
127
+ cls_token_segment_id=0,
128
+ pad_token_segment_id=0,
129
+ sequence_a_segment_id=0,
130
+ mask_padding_with_zero=True):
131
+ # Setting based on the current model type
132
+ cls_token = tokenizer.cls_token
133
+ sep_token = tokenizer.sep_token
134
+ unk_token = tokenizer.unk_token
135
+ pad_token_id = tokenizer.pad_token_id
136
+
137
+ features = []
138
+ for (ex_index, example) in enumerate(examples):
139
+ if ex_index % 5000 == 0:
140
+ logger.info("Writing example %d of %d" % (ex_index, len(examples)))
141
+
142
+ # Tokenize word by word (for NER)
143
+ tokens = []
144
+ slot_labels_ids = []
145
+ for word, slot_label in zip(example.words, example.slot_labels):
146
+ word_tokens = tokenizer.tokenize(word)
147
+ if not word_tokens:
148
+ word_tokens = [unk_token] # For handling the bad-encoded word
149
+ tokens.extend(word_tokens)
150
+ # Use the real label id for the first token of the word, and padding ids for the remaining tokens
151
+ slot_labels_ids.extend([int(slot_label)] + [pad_token_label_id] * (len(word_tokens) - 1))
152
+
153
+ # Account for [CLS] and [SEP]
154
+ special_tokens_count = 2
155
+ if len(tokens) > max_seq_len - special_tokens_count:
156
+ tokens = tokens[:(max_seq_len - special_tokens_count)]
157
+ slot_labels_ids = slot_labels_ids[:(max_seq_len - special_tokens_count)]
158
+
159
+ # Add [SEP] token
160
+ tokens += [sep_token]
161
+ slot_labels_ids += [pad_token_label_id]
162
+ token_type_ids = [sequence_a_segment_id] * len(tokens)
163
+
164
+ # Add [CLS] token
165
+ tokens = [cls_token] + tokens
166
+ slot_labels_ids = [pad_token_label_id] + slot_labels_ids
167
+ token_type_ids = [cls_token_segment_id] + token_type_ids
168
+
169
+ input_ids = tokenizer.convert_tokens_to_ids(tokens)
170
+
171
+ # The mask has 1 for real tokens and 0 for padding tokens. Only real
172
+ # tokens are attended to.
173
+ attention_mask = [1 if mask_padding_with_zero else 0] * len(input_ids)
174
+
175
+ # Zero-pad up to the sequence length.
176
+ padding_length = max_seq_len - len(input_ids)
177
+ input_ids = input_ids + ([pad_token_id] * padding_length)
178
+ attention_mask = attention_mask + ([0 if mask_padding_with_zero else 1] * padding_length)
179
+ token_type_ids = token_type_ids + ([pad_token_segment_id] * padding_length)
180
+ slot_labels_ids = slot_labels_ids + ([pad_token_label_id] * padding_length)
181
+
182
+ assert len(input_ids) == max_seq_len, "Error with input length {} vs {}".format(len(input_ids), max_seq_len)
183
+ assert len(attention_mask) == max_seq_len, "Error with attention mask length {} vs {}".format(len(attention_mask), max_seq_len)
184
+ assert len(token_type_ids) == max_seq_len, "Error with token type length {} vs {}".format(len(token_type_ids), max_seq_len)
185
+ assert len(slot_labels_ids) == max_seq_len, "Error with slot labels length {} vs {}".format(len(slot_labels_ids), max_seq_len)
186
+
187
+ intent_label_id = int(example.intent_label)
188
+
189
+ if ex_index < 5:
190
+ logger.info("*** Example ***")
191
+ logger.info("guid: %s" % example.guid)
192
+ logger.info("tokens: %s" % " ".join([str(x) for x in tokens]))
193
+ logger.info("input_ids: %s" % " ".join([str(x) for x in input_ids]))
194
+ logger.info("attention_mask: %s" % " ".join([str(x) for x in attention_mask]))
195
+ logger.info("token_type_ids: %s" % " ".join([str(x) for x in token_type_ids]))
196
+ logger.info("intent_label: %s (id = %d)" % (example.intent_label, intent_label_id))
197
+ logger.info("slot_labels: %s" % " ".join([str(x) for x in slot_labels_ids]))
198
+
199
+ features.append(
200
+ InputFeatures(input_ids=input_ids,
201
+ attention_mask=attention_mask,
202
+ token_type_ids=token_type_ids,
203
+ intent_label_id=intent_label_id,
204
+ slot_labels_ids=slot_labels_ids
205
+ ))
206
+
207
+ return features
208
+
209
+
210
+ def load_and_cache_examples(args, tokenizer, mode):
211
+ processor = processors[args.task](args)
212
+
213
+ # Load data features from cache or dataset file
214
+ cached_features_file = os.path.join(
215
+ args.data_dir,
216
+ 'cached_{}_{}_{}_{}'.format(
217
+ mode,
218
+ args.task,
219
+ list(filter(None, args.model_name_or_path.split("/"))).pop(),
220
+ args.max_seq_len
221
+ )
222
+ )
223
+
224
+ if os.path.exists(cached_features_file):
225
+ logger.info("Loading features from cached file %s", cached_features_file)
226
+ features = torch.load(cached_features_file)
227
+ else:
228
+ # Load data features from dataset file
229
+ logger.info("Creating features from dataset file at %s", args.data_dir)
230
+ if mode == "train":
231
+ examples = processor.get_examples("train")
232
+ elif mode == "dev":
233
+ examples = processor.get_examples("dev")
234
+ elif mode == "test":
235
+ examples = processor.get_examples("test")
236
+ else:
237
+ raise Exception("For mode, Only train, dev, test is available")
238
+
239
+ # Use cross entropy ignore index as padding label id so that only real label ids contribute to the loss later
240
+ pad_token_label_id = args.ignore_index
241
+ features = convert_examples_to_features(examples, args.max_seq_len, tokenizer,
242
+ pad_token_label_id=pad_token_label_id)
243
+ logger.info("Saving features into cached file %s", cached_features_file)
244
+ torch.save(features, cached_features_file)
245
+
246
+ # Convert to Tensors and build dataset
247
+ all_input_ids = torch.tensor([f.input_ids for f in features], dtype=torch.long)
248
+ all_attention_mask = torch.tensor([f.attention_mask for f in features], dtype=torch.long)
249
+ all_token_type_ids = torch.tensor([f.token_type_ids for f in features], dtype=torch.long)
250
+ all_intent_label_ids = torch.tensor([f.intent_label_id for f in features], dtype=torch.long)
251
+ all_slot_labels_ids = torch.tensor([f.slot_labels_ids for f in features], dtype=torch.long)
252
+
253
+ dataset = TensorDataset(all_input_ids, all_attention_mask,
254
+ all_token_type_ids, all_intent_label_ids, all_slot_labels_ids)
255
+ return dataset
JointBERT-master/main.py ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import argparse
2
+
3
+ from trainer import Trainer
4
+ from utils import init_logger, load_tokenizer, read_prediction_text, set_seed, MODEL_CLASSES, MODEL_PATH_MAP
5
+ from data_loader import load_and_cache_examples
6
+
7
+
8
+ def main(args):
9
+ init_logger()
10
+ set_seed(args)
11
+ tokenizer = load_tokenizer(args)
12
+
13
+ train_dataset = load_and_cache_examples(args, tokenizer, mode="train")
14
+ dev_dataset = load_and_cache_examples(args, tokenizer, mode="dev")
15
+ test_dataset = load_and_cache_examples(args, tokenizer, mode="test")
16
+
17
+ trainer = Trainer(args, train_dataset, dev_dataset, test_dataset)
18
+
19
+ if args.do_train:
20
+ trainer.train()
21
+
22
+ if args.do_eval:
23
+ trainer.load_model()
24
+ trainer.evaluate("test")
25
+
26
+
27
+ if __name__ == '__main__':
28
+ parser = argparse.ArgumentParser()
29
+
30
+ parser.add_argument("--task", default=None, required=True, type=str, help="The name of the task to train")
31
+ parser.add_argument("--model_dir", default=None, required=True, type=str, help="Path to save, load model")
32
+ parser.add_argument("--data_dir", default="./data", type=str, help="The input data dir")
33
+ parser.add_argument("--intent_label_file", default="intent_label.txt", type=str, help="Intent Label file")
34
+ parser.add_argument("--slot_label_file", default="slot_label.txt", type=str, help="Slot Label file")
35
+
36
+ parser.add_argument("--model_type", default="bert", type=str, help="Model type selected in the list: " + ", ".join(MODEL_CLASSES.keys()))
37
+
38
+ parser.add_argument('--seed', type=int, default=1234, help="random seed for initialization")
39
+ parser.add_argument("--train_batch_size", default=32, type=int, help="Batch size for training.")
40
+ parser.add_argument("--eval_batch_size", default=64, type=int, help="Batch size for evaluation.")
41
+ parser.add_argument("--max_seq_len", default=50, type=int, help="The maximum total input sequence length after tokenization.")
42
+ parser.add_argument("--learning_rate", default=5e-5, type=float, help="The initial learning rate for Adam.")
43
+ parser.add_argument("--num_train_epochs", default=10.0, type=float, help="Total number of training epochs to perform.")
44
+ parser.add_argument("--weight_decay", default=0.0, type=float, help="Weight decay if we apply some.")
45
+ parser.add_argument('--gradient_accumulation_steps', type=int, default=1,
46
+ help="Number of updates steps to accumulate before performing a backward/update pass.")
47
+ parser.add_argument("--adam_epsilon", default=1e-8, type=float, help="Epsilon for Adam optimizer.")
48
+ parser.add_argument("--max_grad_norm", default=1.0, type=float, help="Max gradient norm.")
49
+ parser.add_argument("--max_steps", default=-1, type=int, help="If > 0: set total number of training steps to perform. Override num_train_epochs.")
50
+ parser.add_argument("--warmup_steps", default=0, type=int, help="Linear warmup over warmup_steps.")
51
+ parser.add_argument("--dropout_rate", default=0.1, type=float, help="Dropout for fully-connected layers")
52
+
53
+ parser.add_argument('--logging_steps', type=int, default=200, help="Log every X updates steps.")
54
+ parser.add_argument('--save_steps', type=int, default=200, help="Save checkpoint every X updates steps.")
55
+
56
+ parser.add_argument("--do_train", action="store_true", help="Whether to run training.")
57
+ parser.add_argument("--do_eval", action="store_true", help="Whether to run eval on the test set.")
58
+ parser.add_argument("--no_cuda", action="store_true", help="Avoid using CUDA when available")
59
+
60
+ parser.add_argument("--ignore_index", default=0, type=int,
61
+ help='Specifies a target value that is ignored and does not contribute to the input gradient')
62
+
63
+ parser.add_argument('--slot_loss_coef', type=float, default=1.0, help='Coefficient for the slot loss.')
64
+
65
+ # CRF option
66
+ parser.add_argument("--use_crf", action="store_true", help="Whether to use CRF")
67
+ parser.add_argument("--slot_pad_label", default="PAD", type=str, help="Pad token for slot label pad (to be ignore when calculate loss)")
68
+
69
+ args = parser.parse_args()
70
+
71
+ args.model_name_or_path = MODEL_PATH_MAP[args.model_type]
72
+ main(args)
JointBERT-master/model/__init__.py ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ from .modeling_jointbert import JointBERT
2
+ from .modeling_jointdistilbert import JointDistilBERT
3
+ from .modeling_jointalbert import JointAlbert
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