system HF staff commited on
Commit
a21b4e9
0 Parent(s):

Update files from the datasets library (from 1.2.0)

Browse files

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ *.7z filter=lfs diff=lfs merge=lfs -text
2
+ *.arrow filter=lfs diff=lfs merge=lfs -text
3
+ *.bin filter=lfs diff=lfs merge=lfs -text
4
+ *.bin.* filter=lfs diff=lfs merge=lfs -text
5
+ *.bz2 filter=lfs diff=lfs merge=lfs -text
6
+ *.ftz filter=lfs diff=lfs merge=lfs -text
7
+ *.gz filter=lfs diff=lfs merge=lfs -text
8
+ *.h5 filter=lfs diff=lfs merge=lfs -text
9
+ *.joblib filter=lfs diff=lfs merge=lfs -text
10
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
11
+ *.model filter=lfs diff=lfs merge=lfs -text
12
+ *.msgpack filter=lfs diff=lfs merge=lfs -text
13
+ *.onnx filter=lfs diff=lfs merge=lfs -text
14
+ *.ot filter=lfs diff=lfs merge=lfs -text
15
+ *.parquet filter=lfs diff=lfs merge=lfs -text
16
+ *.pb filter=lfs diff=lfs merge=lfs -text
17
+ *.pt filter=lfs diff=lfs merge=lfs -text
18
+ *.pth filter=lfs diff=lfs merge=lfs -text
19
+ *.rar filter=lfs diff=lfs merge=lfs -text
20
+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
21
+ *.tar.* filter=lfs diff=lfs merge=lfs -text
22
+ *.tflite filter=lfs diff=lfs merge=lfs -text
23
+ *.tgz filter=lfs diff=lfs merge=lfs -text
24
+ *.xz filter=lfs diff=lfs merge=lfs -text
25
+ *.zip filter=lfs diff=lfs merge=lfs -text
26
+ *.zstandard filter=lfs diff=lfs merge=lfs -text
27
+ *tfevents* filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,137 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ annotations_creators:
3
+ - crowdsourced
4
+ language_creators:
5
+ - found
6
+ languages:
7
+ - zh
8
+ licenses:
9
+ - unknown
10
+ multilinguality:
11
+ - monolingual
12
+ size_categories:
13
+ - 10K<n<100K
14
+ source_datasets:
15
+ - original
16
+ task_categories:
17
+ - structure-prediction
18
+ task_ids:
19
+ - named-entity-recognition
20
+ ---
21
+
22
+ # Dataset Card for MSRA NER
23
+
24
+ ## Table of Contents
25
+ - [Dataset Description](#dataset-description)
26
+ - [Dataset Summary](#dataset-summary)
27
+ - [Supported Tasks](#supported-tasks-and-leaderboards)
28
+ - [Languages](#languages)
29
+ - [Dataset Structure](#dataset-structure)
30
+ - [Data Instances](#data-instances)
31
+ - [Data Fields](#data-instances)
32
+ - [Data Splits](#data-instances)
33
+ - [Dataset Creation](#dataset-creation)
34
+ - [Curation Rationale](#curation-rationale)
35
+ - [Source Data](#source-data)
36
+ - [Annotations](#annotations)
37
+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
38
+ - [Considerations for Using the Data](#considerations-for-using-the-data)
39
+ - [Social Impact of Dataset](#social-impact-of-dataset)
40
+ - [Discussion of Biases](#discussion-of-biases)
41
+ - [Other Known Limitations](#other-known-limitations)
42
+ - [Additional Information](#additional-information)
43
+ - [Dataset Curators](#dataset-curators)
44
+ - [Licensing Information](#licensing-information)
45
+ - [Citation Information](#citation-information)
46
+
47
+ ## Dataset Description
48
+
49
+ - **Homepage:** [Github](https://github.com/OYE93/Chinese-NLP-Corpus/tree/master/NER/MSRA)
50
+ - **Repository:** [Github](https://github.com/OYE93/Chinese-NLP-Corpus)
51
+ - **Paper:**
52
+ - **Leaderboard:**
53
+ - **Point of Contact:**
54
+
55
+ ### Dataset Summary
56
+
57
+ [More Information Needed]
58
+
59
+ ### Supported Tasks and Leaderboards
60
+
61
+ [More Information Needed]
62
+
63
+ ### Languages
64
+
65
+ [More Information Needed]
66
+
67
+ ## Dataset Structure
68
+
69
+ ### Data Instances
70
+
71
+ [More Information Needed]
72
+
73
+ ### Data Fields
74
+
75
+ [More Information Needed]
76
+
77
+ ### Data Splits
78
+
79
+ [More Information Needed]
80
+
81
+ ## Dataset Creation
82
+
83
+ ### Curation Rationale
84
+
85
+ [More Information Needed]
86
+
87
+ ### Source Data
88
+
89
+ #### Initial Data Collection and Normalization
90
+
91
+ [More Information Needed]
92
+
93
+ #### Who are the source language producers?
94
+
95
+ [More Information Needed]
96
+
97
+ ### Annotations
98
+
99
+ #### Annotation process
100
+
101
+ [More Information Needed]
102
+
103
+ #### Who are the annotators?
104
+
105
+ [More Information Needed]
106
+
107
+ ### Personal and Sensitive Information
108
+
109
+ [More Information Needed]
110
+
111
+ ## Considerations for Using the Data
112
+
113
+ ### Social Impact of Dataset
114
+
115
+ [More Information Needed]
116
+
117
+ ### Discussion of Biases
118
+
119
+ [More Information Needed]
120
+
121
+ ### Other Known Limitations
122
+
123
+ [More Information Needed]
124
+
125
+ ## Additional Information
126
+
127
+ ### Dataset Curators
128
+
129
+ [More Information Needed]
130
+
131
+ ### Licensing Information
132
+
133
+ [More Information Needed]
134
+
135
+ ### Citation Information
136
+
137
+ [More Information Needed]
dataset_infos.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"msra_ner": {"description": "The Third International Chinese Language\nProcessing Bakeoff was held in Spring\n2006 to assess the state of the art in two\nimportant tasks: word segmentation and\nnamed entity recognition. Twenty-nine\ngroups submitted result sets in the two\ntasks across two tracks and a total of five\ncorpora. We found strong results in both\ntasks as well as continuing challenges.\n\nMSRA NER is one of the provided dataset.\nThere are three types of NE, PER (person),\nORG (organization) and LOC (location).\nThe dataset is in the BIO scheme.\n\nFor more details see https://faculty.washington.edu/levow/papers/sighan06.pdf\n", "citation": "@inproceedings{levow2006third,\n author = {Gina{-}Anne Levow},\n title = {The Third International Chinese Language Processing Bakeoff: Word\n Segmentation and Named Entity Recognition},\n booktitle = {SIGHAN@COLING/ACL},\n pages = {108--117},\n publisher = {Association for Computational Linguistics},\n year = {2006}\n}\n", "homepage": "https://www.microsoft.com/en-us/download/details.aspx?id=52531", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 7, "names": ["O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "msra_ner", "config_name": "msra_ner", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 33323074, "num_examples": 45001, "dataset_name": "msra_ner"}, "test": {"name": "test", "num_bytes": 2642934, "num_examples": 3443, "dataset_name": "msra_ner"}}, "download_checksums": {"https://raw.githubusercontent.com/OYE93/Chinese-NLP-Corpus/master/NER/MSRA/msra_train_bio.txt": {"num_bytes": 14037265, "checksum": "b403d1318c5289917ad2ca4136279592521684748327e93f1bf49a3845a40ac7"}, "https://raw.githubusercontent.com/OYE93/Chinese-NLP-Corpus/master/NER/MSRA/msra_test_bio.txt": {"num_bytes": 1119341, "checksum": "2be8e580bcb22e9086e4403d82a7ec0f6e18019ebef35b0fd52941724bdf89a3"}}, "download_size": 15156606, "post_processing_size": null, "dataset_size": 35966008, "size_in_bytes": 51122614}}
dummy/msra_ner/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8cd86e780b1f48defab6cea62ca866fa01ba4203906a323c343da1ac0b0e2ff6
3
+ size 447
msra_ner.py ADDED
@@ -0,0 +1,148 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2020 HuggingFace Datasets Authors.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+
16
+ # Lint as: python3
17
+ """Introduction to MSRA NER Dataset"""
18
+
19
+ import logging
20
+
21
+ import datasets
22
+
23
+
24
+ _CITATION = """\
25
+ @inproceedings{levow2006third,
26
+ author = {Gina{-}Anne Levow},
27
+ title = {The Third International Chinese Language Processing Bakeoff: Word
28
+ Segmentation and Named Entity Recognition},
29
+ booktitle = {SIGHAN@COLING/ACL},
30
+ pages = {108--117},
31
+ publisher = {Association for Computational Linguistics},
32
+ year = {2006}
33
+ }
34
+ """
35
+
36
+ _DESCRIPTION = """\
37
+ The Third International Chinese Language
38
+ Processing Bakeoff was held in Spring
39
+ 2006 to assess the state of the art in two
40
+ important tasks: word segmentation and
41
+ named entity recognition. Twenty-nine
42
+ groups submitted result sets in the two
43
+ tasks across two tracks and a total of five
44
+ corpora. We found strong results in both
45
+ tasks as well as continuing challenges.
46
+
47
+ MSRA NER is one of the provided dataset.
48
+ There are three types of NE, PER (person),
49
+ ORG (organization) and LOC (location).
50
+ The dataset is in the BIO scheme.
51
+
52
+ For more details see https://faculty.washington.edu/levow/papers/sighan06.pdf
53
+ """
54
+
55
+ _URL = "https://raw.githubusercontent.com/OYE93/Chinese-NLP-Corpus/master/NER/MSRA/"
56
+ _TRAINING_FILE = "msra_train_bio.txt"
57
+ _TEST_FILE = "msra_test_bio.txt"
58
+
59
+
60
+ class MsraNerConfig(datasets.BuilderConfig):
61
+ """BuilderConfig for MsraNer"""
62
+
63
+ def __init__(self, **kwargs):
64
+ """BuilderConfig for MSRA NER.
65
+
66
+ Args:
67
+ **kwargs: keyword arguments forwarded to super.
68
+ """
69
+ super(MsraNerConfig, self).__init__(**kwargs)
70
+
71
+
72
+ class MsraNer(datasets.GeneratorBasedBuilder):
73
+ """MSRA NER dataset."""
74
+
75
+ BUILDER_CONFIGS = [
76
+ MsraNerConfig(name="msra_ner", version=datasets.Version("1.0.0"), description="MSRA NER dataset"),
77
+ ]
78
+
79
+ def _info(self):
80
+ return datasets.DatasetInfo(
81
+ description=_DESCRIPTION,
82
+ features=datasets.Features(
83
+ {
84
+ "id": datasets.Value("string"),
85
+ "tokens": datasets.Sequence(datasets.Value("string")),
86
+ "ner_tags": datasets.Sequence(
87
+ datasets.features.ClassLabel(
88
+ names=[
89
+ "O",
90
+ "B-PER",
91
+ "I-PER",
92
+ "B-ORG",
93
+ "I-ORG",
94
+ "B-LOC",
95
+ "I-LOC",
96
+ ]
97
+ )
98
+ ),
99
+ }
100
+ ),
101
+ supervised_keys=None,
102
+ homepage="https://www.microsoft.com/en-us/download/details.aspx?id=52531",
103
+ citation=_CITATION,
104
+ )
105
+
106
+ def _split_generators(self, dl_manager):
107
+ """Returns SplitGenerators."""
108
+ urls_to_download = {
109
+ "train": f"{_URL}{_TRAINING_FILE}",
110
+ "test": f"{_URL}{_TEST_FILE}",
111
+ }
112
+ downloaded_files = dl_manager.download_and_extract(urls_to_download)
113
+
114
+ return [
115
+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
116
+ datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
117
+ ]
118
+
119
+ def _generate_examples(self, filepath):
120
+ logging.info("⏳ Generating examples from = %s", filepath)
121
+ with open(filepath, encoding="utf-8") as f:
122
+ guid = 0
123
+ tokens = []
124
+ ner_tags = []
125
+ for line in f:
126
+ line_stripped = line.strip()
127
+ if line_stripped == "":
128
+ if tokens:
129
+ yield guid, {
130
+ "id": str(guid),
131
+ "tokens": tokens,
132
+ "ner_tags": ner_tags,
133
+ }
134
+ guid += 1
135
+ tokens = []
136
+ ner_tags = []
137
+ else:
138
+ splits = line_stripped.split("\t")
139
+ if len(splits) == 1:
140
+ splits.append("O")
141
+ tokens.append(splits[0])
142
+ ner_tags.append(splits[1])
143
+ # last example
144
+ yield guid, {
145
+ "id": str(guid),
146
+ "tokens": tokens,
147
+ "ner_tags": ner_tags,
148
+ }