Datasets:
Languages:
English
Multilinguality:
monolingual
Language Creators:
crowdsourced
Annotations Creators:
machine-generated
Source Datasets:
original
License:
| # coding=utf-8 | |
| # 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. | |
| """Ollie""" | |
| import bz2 | |
| import datasets | |
| _CITATION = """\ | |
| @inproceedings{ollie-emnlp12, | |
| author = {Mausam and Michael Schmitz and Robert Bart and Stephen Soderland and Oren Etzioni}, | |
| title = {Open Language Learning for Information Extraction}, | |
| booktitle = {Proceedings of Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CONLL)}, | |
| year = {2012} | |
| }""" | |
| _DESCRIPTION = """The Ollie dataset includes two configs for the data | |
| used to train the Ollie informatation extraction algorithm, for 18M | |
| sentences and 3M sentences respectively. | |
| This data is for academic use only. From the authors: | |
| Ollie is a program that automatically identifies and extracts binary | |
| relationships from English sentences. Ollie is designed for Web-scale | |
| information extraction, where target relations are not specified in | |
| advance. | |
| Ollie is our second-generation information extraction system . Whereas | |
| ReVerb operates on flat sequences of tokens, Ollie works with the | |
| tree-like (graph with only small cycles) representation using | |
| Stanford's compression of the dependencies. This allows Ollie to | |
| capture expression that ReVerb misses, such as long-range relations. | |
| Ollie also captures context that modifies a binary relation. Presently | |
| Ollie handles attribution (He said/she believes) and enabling | |
| conditions (if X then). | |
| More information is available at the Ollie homepage: | |
| https://knowitall.github.io/ollie/ | |
| """ | |
| _LICENSE = """The University of Washington acamdemic license: | |
| https://raw.githubusercontent.com/knowitall/ollie/master/LICENSE | |
| """ | |
| _URLs = { | |
| "ollie_lemmagrep": "http://knowitall.cs.washington.edu/ollie/data/lemmagrep.txt.bz2", | |
| "ollie_patterned": "http://knowitall.cs.washington.edu/ollie/data/patterned-all.txt.bz2", | |
| } | |
| class Ollie(datasets.GeneratorBasedBuilder): | |
| """Ollie dataset for knowledge bases and knowledge graphs and underlying sentences.""" | |
| VERSION = datasets.Version("0.1.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig(name="ollie_lemmagrep", description="The Ollie training data", version="1.1.0"), | |
| datasets.BuilderConfig( | |
| name="ollie_patterned", description="The Ollie data used in the Ollie paper.", version="1.1.0" | |
| ), | |
| ] | |
| DEFAULT_CONFIG_NAME = "ollie_lemmagrep" | |
| def _info(self): | |
| if self.config.name == "ollie_lemmagrep": | |
| features = datasets.Features( | |
| { | |
| "arg1": datasets.Value("string"), | |
| "arg2": datasets.Value("string"), | |
| "rel": datasets.Value("string"), | |
| "search_query": datasets.Value("string"), | |
| "sentence": datasets.Value("string"), | |
| "words": datasets.Value("string"), | |
| "pos": datasets.Value("string"), | |
| "chunk": datasets.Value("string"), | |
| "sentence_cnt": datasets.Value("string"), | |
| } | |
| ) | |
| else: | |
| features = datasets.Features( | |
| { | |
| "rel": datasets.Value("string"), | |
| "arg1": datasets.Value("string"), | |
| "arg2": datasets.Value("string"), | |
| "slot0": datasets.Value("string"), | |
| "search_query": datasets.Value("string"), | |
| "pattern": datasets.Value("string"), | |
| "sentence": datasets.Value("string"), | |
| "parse": datasets.Value("string"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| supervised_keys=None, | |
| homepage="https://knowitall.github.io/ollie/", | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| my_urls = _URLs[self.config.name] | |
| data_dir = dl_manager.download_and_extract(my_urls) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": data_dir, | |
| "split": "train", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath, split): | |
| """Yields examples from the Ollie predicates and sentences.""" | |
| with bz2.open(filepath, "rt") as f: | |
| id_ = -1 | |
| if self.config.name == "ollie_lemmagrep": | |
| for row in f: | |
| row = row.strip().split("\t") | |
| id_ += 1 | |
| if len(row) == 8: | |
| yield id_, { | |
| "arg1": row[0].strip(), | |
| "arg2": row[1].strip(), | |
| "rel": "", | |
| "search_query": row[2].strip(), | |
| "sentence": row[3].strip(), | |
| "words": row[4].strip(), | |
| "pos": row[5].strip(), | |
| "chunk": row[6].strip(), | |
| "sentence_cnt": row[7].strip(), | |
| } | |
| else: | |
| yield id_, { | |
| "arg1": row[1].strip(), | |
| "arg2": row[2].strip(), | |
| "rel": row[0].strip(), | |
| "search_query": row[3].strip(), | |
| "sentence": row[4].strip(), | |
| "words": row[5].strip(), | |
| "pos": row[6].strip(), | |
| "chunk": row[7].strip(), | |
| "sentence_cnt": row[8].strip(), | |
| } | |
| else: | |
| for row in f: | |
| row = row.strip().split("\t") | |
| id_ += 1 | |
| if len(row) == 7: | |
| yield id_, { | |
| "rel": row[0].strip(), | |
| "arg1": row[1].strip(), | |
| "arg2": row[2].strip(), | |
| "slot0": "", | |
| "search_query": row[3].strip(), | |
| "pattern": row[4].strip(), | |
| "sentence": row[5].strip(), | |
| "parse": row[6].strip(), | |
| } | |
| else: | |
| yield id_, { | |
| "rel": row[0].strip(), | |
| "arg1": row[1].strip(), | |
| "arg2": row[2].strip(), | |
| "slot0": row[7].strip(), | |
| "search_query": row[3].strip(), | |
| "pattern": row[4].strip(), | |
| "sentence": row[5].strip(), | |
| "parse": row[6].strip(), | |
| } | |