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"""WikiAuto dataset for Text Simplification""" |
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import json |
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import datasets |
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_CITATION = """\ |
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@inproceedings{acl/JiangMLZX20, |
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author = {Chao Jiang and |
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Mounica Maddela and |
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Wuwei Lan and |
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Yang Zhong and |
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Wei Xu}, |
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editor = {Dan Jurafsky and |
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Joyce Chai and |
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Natalie Schluter and |
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Joel R. Tetreault}, |
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title = {Neural {CRF} Model for Sentence Alignment in Text Simplification}, |
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booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational |
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Linguistics, {ACL} 2020, Online, July 5-10, 2020}, |
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pages = {7943--7960}, |
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publisher = {Association for Computational Linguistics}, |
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year = {2020}, |
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url = {https://www.aclweb.org/anthology/2020.acl-main.709/} |
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} |
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""" |
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_DESCRIPTION = """\ |
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WikiAuto provides a set of aligned sentences from English Wikipedia and Simple English Wikipedia |
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as a resource to train sentence simplification systems. The authors first crowd-sourced a set of manual alignments |
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between sentences in a subset of the Simple English Wikipedia and their corresponding versions in English Wikipedia |
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(this corresponds to the `manual` config), then trained a neural CRF system to predict these alignments. |
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The trained model was then applied to the other articles in Simple English Wikipedia with an English counterpart to |
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create a larger corpus of aligned sentences (corresponding to the `auto`, `auto_acl`, `auto_full_no_split`, and `auto_full_with_split` configs here). |
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""" |
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_LICENSE = "CC-BY-SA 3.0" |
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_URLs = { |
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"manual": { |
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"train": "https://www.dropbox.com/sh/ohqaw41v48c7e5p/AACdl4UPKtu7CMMa-CJhz4G7a/wiki-manual/train.tsv?dl=1", |
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"dev": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/dev.tsv", |
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"test": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/test.tsv", |
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}, |
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"auto_acl": { |
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"normal": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/ACL2020/train.src", |
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"simple": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/ACL2020/train.dst", |
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}, |
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"auto_full_no_split": { |
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"normal": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_no_split/train.src", |
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"simple": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_no_split/train.dst", |
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}, |
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"auto_full_with_split": { |
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"normal": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_with_split/train.src", |
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"simple": "https://github.com/chaojiang06/wiki-auto/raw/master/wiki-auto/GEM2021/full_with_split/train.dst", |
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}, |
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"auto": { |
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"part_1": "https://www.dropbox.com/sh/ohqaw41v48c7e5p/AAATBDhU1zpdcT5x5WgO8DMaa/wiki-auto-all-data/wiki-auto-part-1-data.json?dl=1", |
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"part_2": "https://www.dropbox.com/sh/ohqaw41v48c7e5p/AAATgPkjo_tPt9z12vZxJ3MRa/wiki-auto-all-data/wiki-auto-part-2-data.json?dl=1", |
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}, |
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} |
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class WikiAuto(datasets.GeneratorBasedBuilder): |
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"""WikiAuto dataset for sentence simplification""" |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="manual", |
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version=VERSION, |
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description="A set of 10K Wikipedia sentence pairs aligned by crowd workers.", |
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), |
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datasets.BuilderConfig( |
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name="auto_acl", |
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version=VERSION, |
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description="Automatically aligned and filtered sentence pairs used to train the ACL2020 system.", |
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), |
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datasets.BuilderConfig( |
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name="auto_full_no_split", |
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version=VERSION, |
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description="All automatically aligned sentence pairs without sentence splitting.", |
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), |
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datasets.BuilderConfig( |
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name="auto_full_with_split", |
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version=VERSION, |
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description="All automatically aligned sentence pairs with sentence splitting.", |
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), |
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datasets.BuilderConfig( |
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name="auto", version=VERSION, description="A large set of automatically aligned sentence pairs." |
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), |
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] |
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DEFAULT_CONFIG_NAME = "auto" |
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def _info(self): |
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if self.config.name == "manual": |
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features = datasets.Features( |
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{ |
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"alignment_label": datasets.ClassLabel(names=["notAligned", "aligned", "partialAligned"]), |
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"normal_sentence_id": datasets.Value("string"), |
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"simple_sentence_id": datasets.Value("string"), |
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"normal_sentence": datasets.Value("string"), |
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"simple_sentence": datasets.Value("string"), |
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"gleu_score": datasets.Value("float32"), |
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} |
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) |
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elif ( |
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self.config.name == "auto_acl" |
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or self.config.name == "auto_full_no_split" |
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or self.config.name == "auto_full_with_split" |
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): |
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features = datasets.Features( |
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{ |
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"normal_sentence": datasets.Value("string"), |
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"simple_sentence": datasets.Value("string"), |
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} |
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) |
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else: |
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features = datasets.Features( |
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{ |
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"example_id": datasets.Value("string"), |
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"normal": { |
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"normal_article_id": datasets.Value("int32"), |
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"normal_article_title": datasets.Value("string"), |
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"normal_article_url": datasets.Value("string"), |
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"normal_article_content": datasets.Sequence( |
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{ |
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"normal_sentence_id": datasets.Value("string"), |
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"normal_sentence": datasets.Value("string"), |
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} |
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), |
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}, |
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"simple": { |
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"simple_article_id": datasets.Value("int32"), |
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"simple_article_title": datasets.Value("string"), |
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"simple_article_url": datasets.Value("string"), |
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"simple_article_content": datasets.Sequence( |
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{ |
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"simple_sentence_id": datasets.Value("string"), |
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"simple_sentence": datasets.Value("string"), |
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} |
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), |
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}, |
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"paragraph_alignment": datasets.Sequence( |
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{ |
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"normal_paragraph_id": datasets.Value("string"), |
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"simple_paragraph_id": datasets.Value("string"), |
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} |
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), |
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"sentence_alignment": datasets.Sequence( |
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{ |
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"normal_sentence_id": datasets.Value("string"), |
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"simple_sentence_id": datasets.Value("string"), |
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} |
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), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage="https://github.com/chaojiang06/wiki-auto", |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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my_urls = _URLs[self.config.name] |
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data_dir = dl_manager.download_and_extract(my_urls) |
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if self.config.name in ["manual", "auto"]: |
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return [ |
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datasets.SplitGenerator( |
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name=spl, |
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gen_kwargs={ |
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"filepaths": data_dir, |
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"split": spl, |
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}, |
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) |
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for spl in data_dir |
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] |
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else: |
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return [ |
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datasets.SplitGenerator( |
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name="full", |
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gen_kwargs={"filepaths": data_dir, "split": "full"}, |
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) |
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] |
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def _generate_examples(self, filepaths, split): |
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if self.config.name == "manual": |
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keys = [ |
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"alignment_label", |
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"simple_sentence_id", |
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"normal_sentence_id", |
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"simple_sentence", |
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"normal_sentence", |
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"gleu_score", |
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] |
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with open(filepaths[split], encoding="utf-8") as f: |
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for id_, line in enumerate(f): |
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values = line.strip().split("\t") |
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assert len(values) == 6, f"Not enough fields in ---- {line} --- {values}" |
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yield id_, dict( |
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[(k, val) if k != "gleu_score" else (k, float(val)) for k, val in zip(keys, values)] |
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) |
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elif ( |
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self.config.name == "auto_acl" |
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or self.config.name == "auto_full_no_split" |
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or self.config.name == "auto_full_with_split" |
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): |
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with open(filepaths["normal"], encoding="utf-8") as fi: |
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with open(filepaths["simple"], encoding="utf-8") as fo: |
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for id_, (norm_se, simp_se) in enumerate(zip(fi, fo)): |
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yield id_, { |
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"normal_sentence": norm_se, |
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"simple_sentence": simp_se, |
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} |
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else: |
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dataset_dict = json.load(open(filepaths[split], encoding="utf-8")) |
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for id_, (eid, example_dict) in enumerate(dataset_dict.items()): |
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res = { |
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"example_id": eid, |
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"normal": { |
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"normal_article_id": example_dict["normal"]["id"], |
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"normal_article_title": example_dict["normal"]["title"], |
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"normal_article_url": example_dict["normal"]["url"], |
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"normal_article_content": { |
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"normal_sentence_id": [ |
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sen_id for sen_id, sen_txt in example_dict["normal"]["content"].items() |
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], |
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"normal_sentence": [ |
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sen_txt for sen_id, sen_txt in example_dict["normal"]["content"].items() |
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], |
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}, |
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}, |
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"simple": { |
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"simple_article_id": example_dict["simple"]["id"], |
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"simple_article_title": example_dict["simple"]["title"], |
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"simple_article_url": example_dict["simple"]["url"], |
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"simple_article_content": { |
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"simple_sentence_id": [ |
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sen_id for sen_id, sen_txt in example_dict["simple"]["content"].items() |
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], |
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"simple_sentence": [ |
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sen_txt for sen_id, sen_txt in example_dict["simple"]["content"].items() |
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], |
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}, |
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}, |
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"paragraph_alignment": { |
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"normal_paragraph_id": [ |
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norm_id for simp_id, norm_id in example_dict.get("paragraph_alignment", []) |
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], |
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"simple_paragraph_id": [ |
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simp_id for simp_id, norm_id in example_dict.get("paragraph_alignment", []) |
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], |
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}, |
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"sentence_alignment": { |
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"normal_sentence_id": [ |
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norm_id for simp_id, norm_id in example_dict.get("sentence_alignment", []) |
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], |
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"simple_sentence_id": [ |
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simp_id for simp_id, norm_id in example_dict.get("sentence_alignment", []) |
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], |
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}, |
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} |
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yield id_, res |
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