Datasets:
Tasks:
Table to Text
Modalities:
Text
Languages:
English
Size:
10K - 100K
Tags:
data-to-text
License:
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
"""TODO: Add a description here.""" | |
import csv | |
import json | |
import os | |
import datasets | |
_CITATION = """\ | |
@inproceedings{puduppully-etal-2019-data, | |
title = "Data-to-text Generation with Entity Modeling", | |
author = "Puduppully, Ratish and | |
Dong, Li and | |
Lapata, Mirella", | |
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics", | |
month = jul, | |
year = "2019", | |
address = "Florence, Italy", | |
publisher = "Association for Computational Linguistics", | |
url = "https://www.aclweb.org/anthology/P19-1195", | |
doi = "10.18653/v1/P19-1195", | |
pages = "2023--2035", | |
} | |
""" | |
_DESCRIPTION = """\ | |
The MLB dataset for data to text generation contains Major League Baseball games statistics and | |
their human-written summaries. | |
""" | |
_HOMEPAGE = "https://github.com/ratishsp/mlb-data-scripts" | |
_LICENSE = "" | |
_URLs = { | |
"train": "train.jsonl.bz2", | |
"validation": "validation.jsonl.bz2", | |
"test": "test.jsonl.bz2" | |
} | |
class MlbDataToText(datasets.GeneratorBasedBuilder): | |
"""MLB dataset for data to text generation""" | |
VERSION = datasets.Version("1.1.0") | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"home_name": datasets.Value("string"), | |
"box_score": [ | |
{ | |
"p_l": datasets.Value("string"), | |
"last_name": datasets.Value("string"), | |
"p_h": datasets.Value("string"), | |
"sac": datasets.Value("string"), | |
"p_bb": datasets.Value("string"), | |
"pos": datasets.Value("string"), | |
"ao": datasets.Value("string"), | |
"p_bf": datasets.Value("string"), | |
"cs": datasets.Value("string"), | |
"hbp": datasets.Value("string"), | |
"ab": datasets.Value("string"), | |
"full_name": datasets.Value("string"), | |
"p_w": datasets.Value("string"), | |
"go": datasets.Value("string"), | |
"fldg": datasets.Value("string"), | |
"p_bs": datasets.Value("string"), | |
"avg": datasets.Value("string"), | |
"p_r": datasets.Value("string"), | |
"p_s": datasets.Value("string"), | |
"lob": datasets.Value("string"), | |
"first_name": datasets.Value("string"), | |
"p_sv": datasets.Value("string"), | |
"p_so": datasets.Value("string"), | |
"p_save": datasets.Value("string"), | |
"p_hr": datasets.Value("string"), | |
"po": datasets.Value("string"), | |
"p_ip1": datasets.Value("string"), | |
"p_ip2": datasets.Value("string"), | |
"bb": datasets.Value("string"), | |
"ops": datasets.Value("string"), | |
"p_hld": datasets.Value("string"), | |
"bo": datasets.Value("string"), | |
"p_loss": datasets.Value("string"), | |
"e": datasets.Value("string"), | |
"p_game_score": datasets.Value("string"), | |
"p_win": datasets.Value("string"), | |
"a": datasets.Value("string"), | |
"p_era": datasets.Value("string"), | |
"d": datasets.Value("string"), | |
"p_out": datasets.Value("string"), | |
"h": datasets.Value("string"), | |
"p_er": datasets.Value("string"), | |
"p_np": datasets.Value("string"), | |
"hr": datasets.Value("string"), | |
"r": datasets.Value("string"), | |
"so": datasets.Value("string"), | |
"t": datasets.Value("string"), | |
"rbi": datasets.Value("string"), | |
"team": datasets.Value("string"), | |
"sb": datasets.Value("string"), | |
"slg": datasets.Value("string"), | |
"sf": datasets.Value("string"), | |
"obp": datasets.Value("string"), | |
} | |
], | |
"home_city": datasets.Value("string"), | |
"vis_name": datasets.Value("string"), | |
"play_by_play": [{ | |
"top": [{ | |
"runs": datasets.Value("string"), | |
"scorers": [ | |
datasets.Value("string") | |
], | |
"pitcher": datasets.Value("string"), | |
"o": datasets.Value("string"), | |
"b": datasets.Value("string"), | |
"s": datasets.Value("string"), | |
"batter": datasets.Value("string"), | |
"b1": [ | |
datasets.Value("string") | |
], | |
"b2": [ | |
datasets.Value("string") | |
], | |
"b3": [ | |
datasets.Value("string") | |
], | |
"event": datasets.Value("string"), | |
} | |
], | |
"bottom": [{ | |
"runs": datasets.Value("string"), | |
"scorers": [ | |
datasets.Value("string") | |
], | |
"pitcher": datasets.Value("string"), | |
"o": datasets.Value("string"), | |
"b": datasets.Value("string"), | |
"s": datasets.Value("string"), | |
"batter": datasets.Value("string"), | |
"b1": [ | |
datasets.Value("string") | |
], | |
"b2": [ | |
datasets.Value("string") | |
], | |
"b3": [ | |
datasets.Value("string") | |
], | |
"event": datasets.Value("string"), | |
} | |
], | |
"inning": datasets.Value("string") | |
} | |
], | |
"vis_line": { | |
"innings": [{ | |
"inn": datasets.Value("string"), | |
"runs": datasets.Value("string") | |
} | |
], | |
"result": datasets.Value("string"), | |
"team_runs": datasets.Value("string"), | |
"team_hits": datasets.Value("string"), | |
"team_errors": datasets.Value("string"), | |
"team_name": datasets.Value("string"), | |
"team_city": datasets.Value("string") | |
}, | |
"home_line": { | |
"innings": [{ | |
"inn": datasets.Value("string"), | |
"runs": datasets.Value("string") | |
} | |
], | |
"result": datasets.Value("string"), | |
"team_runs": datasets.Value("string"), | |
"team_hits": datasets.Value("string"), | |
"team_errors": datasets.Value("string"), | |
"team_name": datasets.Value("string"), | |
"team_city": datasets.Value("string") | |
}, | |
"vis_city": datasets.Value("string"), | |
"day": datasets.Value("string"), | |
"summary": [ | |
datasets.Value("string"), | |
], | |
"gem_id": datasets.Value("string") | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration | |
# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name | |
# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs | |
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. | |
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive | |
train_dir = dl_manager.download_and_extract(_URLs["train"]) | |
validation_dir = dl_manager.download_and_extract(_URLs["validation"]) | |
test_dir = dl_manager.download_and_extract(_URLs["test"]) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": train_dir, | |
"split": "train", | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": test_dir, | |
"split": "test" | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": validation_dir, | |
"split": "validation", | |
}, | |
), | |
] | |
def _generate_examples( | |
self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
): | |
""" Yields examples as (key, example) tuples. """ | |
# This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. | |
# The `key` is here for legacy reason (tfds) and is not important in itself. | |
with open(filepath, encoding="utf-8") as f: | |
for id_, row in enumerate(f): | |
data = json.loads(row) | |
yield id_, { | |
"home_name": data["home_name"], | |
"box_score": data["box_score"], | |
"home_city": data["home_city"], | |
"vis_name": data["vis_name"], | |
"play_by_play": data["play_by_play"], | |
"vis_line": data["vis_line"], | |
"vis_city": data["vis_city"], | |
"day": data["day"], | |
"home_line": data["home_line"], | |
"summary": data["summary"], | |
"gem_id": data["gem_id"] | |
} | |