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- # coding=utf-8
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- # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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-
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- # Lint as: python3
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- """BLiMP dataset with minimal pairs of grammatical phenomena in English."""
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-
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-
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- import json
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-
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- import datasets
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-
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-
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- _CITATION = """
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- @article{warstadt2019blimp,
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- title={BLiMP: A Benchmark of Linguistic Minimal Pairs for English},
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- author={Warstadt, Alex and Parrish, Alicia and Liu, Haokun and Mohananey, Anhad and Peng, Wei, and Wang, Sheng-Fu and Bowman, Samuel R},
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- journal={arXiv preprint arXiv:1912.00582},
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- year={2019}
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- }
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- """
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-
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- _DESCRIPTION = """
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- BLiMP is a challenge set for evaluating what language models (LMs) know about
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- major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
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- containing 1000 minimal pairs isolating specific contrasts in syntax,
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- morphology, or semantics. The data is automatically generated according to
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- expert-crafted grammars.
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- """
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-
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- _PROJECT_URL = "https://github.com/alexwarstadt/blimp/tree/master/"
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- _DOWNLOAD_URL = "https://raw.githubusercontent.com/alexwarstadt/blimp/master/"
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-
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-
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- class BlimpConfig(datasets.BuilderConfig):
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- """BuilderConfig for Blimp."""
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-
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- def __init__(self, name, version=datasets.Version("0.1.0"), **kwargs):
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- """BuilderConfig for Blimp.
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-
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- Args:
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- name (str): UID of the linguistic paradigm
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- **kwargs: keyword arguments forwarded to super.
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- """
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- description = _DESCRIPTION
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- description += f"This configuration includes the paradigm {name}."
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-
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- super().__init__(name=name, description=description, version=version, **kwargs)
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-
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-
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- class Blimp(datasets.GeneratorBasedBuilder):
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- """Minimal grammatical and ungrammatical pairs of 67 linguistic paradigms."""
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-
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- all_paradigms = [
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- "adjunct_island",
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- "anaphor_gender_agreement",
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- "anaphor_number_agreement",
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- "animate_subject_passive",
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- "animate_subject_trans",
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- "causative",
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- "complex_NP_island",
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- "coordinate_structure_constraint_complex_left_branch",
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- "coordinate_structure_constraint_object_extraction",
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- "determiner_noun_agreement_1",
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- "determiner_noun_agreement_2",
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- "determiner_noun_agreement_irregular_1",
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- "determiner_noun_agreement_irregular_2",
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- "determiner_noun_agreement_with_adj_2",
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- "determiner_noun_agreement_with_adj_irregular_1",
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- "determiner_noun_agreement_with_adj_irregular_2",
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- "determiner_noun_agreement_with_adjective_1",
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- "distractor_agreement_relational_noun",
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- "distractor_agreement_relative_clause",
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- "drop_argument",
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- "ellipsis_n_bar_1",
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- "ellipsis_n_bar_2",
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- "existential_there_object_raising",
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- "existential_there_quantifiers_1",
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- "existential_there_quantifiers_2",
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- "existential_there_subject_raising",
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- "expletive_it_object_raising",
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- "inchoative",
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- "intransitive",
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- "irregular_past_participle_adjectives",
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- "irregular_past_participle_verbs",
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- "irregular_plural_subject_verb_agreement_1",
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- "irregular_plural_subject_verb_agreement_2",
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- "left_branch_island_echo_question",
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- "left_branch_island_simple_question",
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- "matrix_question_npi_licensor_present",
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- "npi_present_1",
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- "npi_present_2",
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- "only_npi_licensor_present",
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- "only_npi_scope",
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- "passive_1",
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- "passive_2",
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- "principle_A_c_command",
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- "principle_A_case_1",
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- "principle_A_case_2",
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- "principle_A_domain_1",
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- "principle_A_domain_2",
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- "principle_A_domain_3",
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- "principle_A_reconstruction",
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- "regular_plural_subject_verb_agreement_1",
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- "regular_plural_subject_verb_agreement_2",
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- "sentential_negation_npi_licensor_present",
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- "sentential_negation_npi_scope",
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- "sentential_subject_island",
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- "superlative_quantifiers_1",
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- "superlative_quantifiers_2",
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- "tough_vs_raising_1",
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- "tough_vs_raising_2",
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- "transitive",
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- "wh_island",
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- "wh_questions_object_gap",
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- "wh_questions_subject_gap",
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- "wh_questions_subject_gap_long_distance",
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- "wh_vs_that_no_gap",
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- "wh_vs_that_no_gap_long_distance",
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- "wh_vs_that_with_gap",
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- "wh_vs_that_with_gap_long_distance",
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- ]
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-
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- BUILDER_CONFIGS = [BlimpConfig(paradigm) for paradigm in all_paradigms]
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-
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- def _info(self):
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=datasets.Features(
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- {
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- "sentence_good": datasets.Value("string"),
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- "sentence_bad": datasets.Value("string"),
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- "field": datasets.Value("string"),
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- "linguistics_term": datasets.Value("string"),
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- "UID": datasets.Value("string"),
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- "simple_LM_method": datasets.Value("bool"),
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- "one_prefix_method": datasets.Value("bool"),
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- "two_prefix_method": datasets.Value("bool"),
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- "lexically_identical": datasets.Value("bool"),
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- "pair_id": datasets.Value("int32"),
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- }
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- ),
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- homepage=_PROJECT_URL,
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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- download_urls = _DOWNLOAD_URL + f"data/{self.config.name}.jsonl"
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- downloaded_file = dl_manager.download_and_extract(download_urls)
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- return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file})]
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-
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- def _generate_examples(self, filepath):
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- """Yields examples."""
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- with open(filepath, "r", encoding="utf-8") as f:
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- for line in f:
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- line_dict = json.loads(line)
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- id_ = line_dict["UID"] + "_" + line_dict["pairID"]
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- feats = {
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- "sentence_good": line_dict["sentence_good"],
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- "sentence_bad": line_dict["sentence_bad"],
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- "field": line_dict["field"],
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- "linguistics_term": line_dict["linguistics_term"],
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- "UID": line_dict["UID"],
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- "simple_LM_method": line_dict["simple_LM_method"],
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- "one_prefix_method": line_dict["one_prefix_method"],
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- "two_prefix_method": line_dict["two_prefix_method"],
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- "lexically_identical": line_dict["lexically_identical"],
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- "pair_id": int(line_dict["pairID"]),
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- }
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- yield id_, feats