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", | |
| "validation": "validation.jsonl", | |
| "test": "test.jsonl" | |
| } | |
| 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"), | |
| "event2": datasets.Value("string"), | |
| "home_team_runs": datasets.Value("string"), | |
| "away_team_runs": datasets.Value("string"), | |
| "rbi": datasets.Value("string"), | |
| "error_runs": datasets.Value("string"), | |
| "fielder_error": 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"), | |
| "event2": datasets.Value("string"), | |
| "home_team_runs": datasets.Value("string"), | |
| "away_team_runs": datasets.Value("string"), | |
| "rbi": datasets.Value("string"), | |
| "error_runs": datasets.Value("string"), | |
| "fielder_error": 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"] | |
| } | |