Upload multitacred.py

multitacred.py

@@ -0,0 +1,451 @@
+# coding=utf-8
+# Copyright 2022 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.
+
+"""The MultiTACRED Relation Classification dataset in various languages"""
+import itertools
+import json
+import os
+
+import datasets
+
+_CITATION = """\
+@inproceedings{hennig-etal-2023-multitacred,
+    title = "MultiTACRED: A Multilingual Version of the TAC Relation Extraction Dataset",
+    author = "Hennig, Leonhard and Thomas, Philippe and Möller, Sebastian",
+    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    month = jul,
+    year = "2023",
+    address = "Online and Toronto, Canada",
+    publisher = "Association for Computational Linguistics",
+}
+
+@inproceedings{zhang-etal-2017-position,
+    title = "Position-aware Attention and Supervised Data Improve Slot Filling",
+    author = "Zhang, Yuhao  and
+      Zhong, Victor  and
+      Chen, Danqi  and
+      Angeli, Gabor  and
+      Manning, Christopher D.",
+    booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
+    month = sep,
+    year = "2017",
+    address = "Copenhagen, Denmark",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/D17-1004",
+    doi = "10.18653/v1/D17-1004",
+    pages = "35--45",
+}
+
+@inproceedings{alt-etal-2020-tacred,
+    title = "{TACRED} Revisited: A Thorough Evaluation of the {TACRED} Relation Extraction Task",
+    author = "Alt, Christoph  and
+      Gabryszak, Aleksandra  and
+      Hennig, Leonhard",
+    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
+    month = jul,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/2020.acl-main.142",
+    doi = "10.18653/v1/2020.acl-main.142",
+    pages = "1558--1569",
+}
+
+@inproceedings{DBLP:conf/aaai/StoicaPP21,
+  author       = {George Stoica and
+                  Emmanouil Antonios Platanios and
+                  Barnab{\'{a}}s P{\'{o}}czos},
+  title        = {Re-TACRED: Addressing Shortcomings of the {TACRED} Dataset},
+  booktitle    = {Thirty-Fifth {AAAI} Conference on Artificial Intelligence, {AAAI}
+                  2021, Thirty-Third Conference on Innovative Applications of Artificial
+                  Intelligence, {IAAI} 2021, The Eleventh Symposium on Educational Advances
+                  in Artificial Intelligence, {EAAI} 2021, Virtual Event, February 2-9,
+                  2021},
+  pages        = {13843--13850},
+  publisher    = {{AAAI} Press},
+  year         = {2021},
+  url          = {https://ojs.aaai.org/index.php/AAAI/article/view/17631},
+}
+"""
+
+_DESCRIPTION = """\
+MultiTACRED is a multilingual version of the large-scale TAC Relation Extraction Dataset (LDC2018T24). 
+It covers 12 typologically diverse languages from 9 language families, and was created by the Speech & Language 
+Technology group of DFKI by machine-translating the  instances of the original TACRED dataset and automatically 
+projecting their entity annotations. For details of the original TACRED's data collection and annotation process, 
+see LDC2018T24. Translations are syntactically validated by checking the correctness of the XML tag markup. 
+Any translations with an invalid tag structure, e.g. missing or invalid head or tail tag pairs, are 
+discarded (on average, 2.3% of the instances).
+
+Languages covered are: Arabic, Chinese, Finnish, French, German, Hindi, Hungarian, Japanese, Polish,
+ Russian, Spanish, Turkish. Intended use is supervised relation classification. Audience - researchers.
+
+ Please see our ACL paper for full details.
+
+NOTE: This Datasetreader supports a reduced version of the original TACRED JSON format with the following changes:
+- Removed fields: stanford_pos, stanford_ner, stanford_head, stanford_deprel, docid
+The motivation for this is that we want to support additional languages, for which these fields were not required
+or available. The reader expects the specification of a language-specific configuration specifying the variant
+(original, revisited or retacred) and the language (as a two-letter iso code). The default config is 'original-de'.
+
+The DatasetReader changes the offsets of the following fields, to conform with standard Python usage (see
+#_generate_examples()):
+- subj_end to subj_end + 1 (make end offset exclusive)
+- obj_end to obj_end + 1 (make end offset exclusive)
+
+NOTE 2: The MultiTACRED dataset offers an additional 'split', namely the backtranslated test data (translated to target
+language and then back to English). To access this split, access dataset['backtranslated_test'].
+"""
+
+_HOMEPAGE = "https://github.com/DFKI-NLP/MultiTACRED"
+
+_LICENSE = "LDC"
+
+_URL = "https://catalog.ldc.upenn.edu/LDC2023_TODO"
+
+# The HuggingFace dataset library don't host the datasets but only point to the original files
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_PATCH_URLs = {
+    "dev": "https://raw.githubusercontent.com/DFKI-NLP/tacrev/master/patch/dev_patch.json",
+    "test": "https://raw.githubusercontent.com/DFKI-NLP/tacrev/master/patch/test_patch.json",
+}
+_RETACRED_PATCH_URLs = {
+    "train": "https://raw.githubusercontent.com/gstoica27/Re-TACRED/master/Re-TACRED/train_id2label.json",
+    "dev": "https://raw.githubusercontent.com/gstoica27/Re-TACRED/master/Re-TACRED/dev_id2label.json",
+    "test": "https://raw.githubusercontent.com/gstoica27/Re-TACRED/master/Re-TACRED/test_id2label.json"
+}
+
+_BACKTRANSLATION_TEST_SPLIT = "backtranslated_test"
+
+_RETACRED = "retacred"
+
+_REVISITED = "revisited"
+
+_ORIGINAL = "original"
+
+_VERSION = datasets.Version("1.1.0")
+
+_LANGS = [
+    "ar",
+    "de",
+    "es",
+    "fi",
+    "fr",
+    "hi",
+    "hu",
+    "ja",
+    "pl",
+    "ru",
+    "tr",
+    "zh",
+]
+
+_CLASS_LABELS = [
+    "no_relation",
+    "org:alternate_names",
+    "org:city_of_headquarters",
+    "org:country_of_headquarters",
+    "org:dissolved",
+    "org:founded",
+    "org:founded_by",
+    "org:member_of",
+    "org:members",
+    "org:number_of_employees/members",
+    "org:parents",
+    "org:political/religious_affiliation",
+    "org:shareholders",
+    "org:stateorprovince_of_headquarters",
+    "org:subsidiaries",
+    "org:top_members/employees",
+    "org:website",
+    "per:age",
+    "per:alternate_names",
+    "per:cause_of_death",
+    "per:charges",
+    "per:children",
+    "per:cities_of_residence",
+    "per:city_of_birth",
+    "per:city_of_death",
+    "per:countries_of_residence",
+    "per:country_of_birth",
+    "per:country_of_death",
+    "per:date_of_birth",
+    "per:date_of_death",
+    "per:employee_of",
+    "per:origin",
+    "per:other_family",
+    "per:parents",
+    "per:religion",
+    "per:schools_attended",
+    "per:siblings",
+    "per:spouse",
+    "per:stateorprovince_of_birth",
+    "per:stateorprovince_of_death",
+    "per:stateorprovinces_of_residence",
+    "per:title",
+]
+
+_RETACRED_CLASS_LABELS = [
+    "no_relation",
+    "org:alternate_names",
+    "org:city_of_branch",
+    "org:country_of_branch",
+    "org:dissolved",
+    "org:founded",
+    "org:founded_by",
+    "org:member_of",
+    "org:members",
+    "org:number_of_employees/members",
+    "org:political/religious_affiliation",
+    "org:shareholders",
+    "org:stateorprovince_of_branch",
+    "org:top_members/employees",
+    "org:website",
+    "per:age",
+    "per:cause_of_death",
+    "per:charges",
+    "per:children",
+    "per:cities_of_residence",
+    "per:city_of_birth",
+    "per:city_of_death",
+    "per:countries_of_residence",
+    "per:country_of_birth",
+    "per:country_of_death",
+    "per:date_of_birth",
+    "per:date_of_death",
+    "per:employee_of",
+    "per:identity",
+    "per:origin",
+    "per:other_family",
+    "per:parents",
+    "per:religion",
+    "per:schools_attended",
+    "per:siblings",
+    "per:spouse",
+    "per:stateorprovince_of_birth",
+    "per:stateorprovince_of_death",
+    "per:stateorprovinces_of_residence",
+    "per:title"
+]
+
+_NER_CLASS_LABELS = [
+    "LOCATION",
+    "ORGANIZATION",
+    "PERSON",
+    "DATE",
+    "MONEY",
+    "PERCENT",
+    "TIME",
+    "CAUSE_OF_DEATH",
+    "CITY",
+    "COUNTRY",
+    "CRIMINAL_CHARGE",
+    "EMAIL",
+    "HANDLE",
+    "IDEOLOGY",
+    "NATIONALITY",
+    "RELIGION",
+    "STATE_OR_PROVINCE",
+    "TITLE",
+    "URL",
+    "NUMBER",
+    "ORDINAL",
+    "MISC",
+    "DURATION",
+    "O",
+]
+
+_DESC_TEXTS = {_ORIGINAL: 'The original TACRED.',
+                _REVISITED: 'TACRED Revisited (corrected labels for 5k most challenging examples in dev and test split).',
+                _RETACRED: 'Relabeled TACRED (corrected labels for all splits and pruned)'}
+
+
+def convert_ptb_token(token: str) -> str:
+    """Convert PTB tokens to normal tokens"""
+    return {
+        "-lrb-": "(",
+        "-rrb-": ")",
+        "-lsb-": "[",
+        "-rsb-": "]",
+        "-lcb-": "{",
+        "-rcb-": "}",
+    }.get(token.lower(), token)
+
+
+class MultiTacredConfig(datasets.BuilderConfig):
+    """BuilderConfig for MultiTacred."""
+
+    def __init__(self, label_variant, language, **kwargs):
+        """BuilderConfig for MultiTacred.
+        Args:
+          label_variant: `string`, source of labels, i.e. ORIGINAL, REVISITED or RETACRED
+          language: `string`, 2-letter ISO 639-1 language code
+          **kwargs: keyword arguments forwarded to super.
+        """
+
+        super(MultiTacredConfig, self).__init__(version=_VERSION, **kwargs)
+        self.language = language
+        self.label_variant = label_variant
+
+
+class MultiTacred(datasets.GeneratorBasedBuilder):
+    """MultiTACRED is a multilingual version of the large-scale TAC Relation Extraction Dataset (LDC2018T24)."""
+
+    BUILDER_CONFIGS = [
+        MultiTacredConfig(
+            name=f"{label_variant}-{language}",
+            language=language,
+            label_variant=label_variant,
+            description=f"{_DESC_TEXTS[label_variant]} examples in language '{language}'.",
+        )
+        for (language, label_variant) in itertools.product(_LANGS, [_ORIGINAL, _REVISITED, _RETACRED])
+    ]
+
+    DEFAULT_CONFIG_NAME = "original-de"  # type: ignore
+
+    @property
+    def manual_download_instructions(self):
+        return (
+            "To use MultiTACRED you have to download it manually. "
+            "It is available via the LDC at https://catalog.ldc.upenn.edu/LDC2023_TODO"
+            "Please extract all files in one folder and load the a language with: "
+            "`datasets.load_dataset('DFKI-SLT/multitacred', name=variant/lang, data_dir='path/to/folder/folder_name')`."
+        )
+
+    def _info(self):
+
+        features = datasets.Features(
+            {
+                "id": datasets.Value("string"),
+                "token": datasets.Sequence(datasets.Value("string")),
+                "subj_start": datasets.Value("int32"),
+                "subj_end": datasets.Value("int32"),
+                "subj_type": datasets.ClassLabel(names=_NER_CLASS_LABELS),
+                "obj_start": datasets.Value("int32"),
+                "obj_end": datasets.Value("int32"),
+                "obj_type": datasets.ClassLabel(names=_NER_CLASS_LABELS),
+                "relation": datasets.ClassLabel(
+                    names=_RETACRED_CLASS_LABELS if self.config.label_variant == _RETACRED else _CLASS_LABELS),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # 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
+        patch_files = {}
+        if self.config.label_variant == _REVISITED:
+            patch_files = dl_manager.download_and_extract(_PATCH_URLs)
+        elif self.config.label_variant == _RETACRED:
+            patch_files = dl_manager.download_and_extract(_RETACRED_PATCH_URLs)
+
+        data_dir = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
+
+        if not os.path.exists(data_dir):
+            raise FileNotFoundError(
+                "{} does not exist. Make sure you insert a manual dir via `datasets.load_dataset("
+                "'DFKI-SLT/multitacred', name=..., data_dir=...)` that includes the unzipped files from the "
+                "MULTITACRED_LDC zip. Manual download instructions: {}".format(
+                    data_dir, self.manual_download_instructions
+                )
+            )
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, self.config.language, f"train_{self.config.language}.json"),
+                    "patch_filepath": patch_files.get("train"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, self.config.language, f"test_{self.config.language}.json"),
+                    "patch_filepath": patch_files.get("test"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, self.config.language, f"dev_{self.config.language}.json"),
+                    "patch_filepath": patch_files.get("dev"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=_BACKTRANSLATION_TEST_SPLIT,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, self.config.language, f"test_en_{self.config.language}_bt.json"),
+                    "patch_filepath": patch_files.get("test"),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, patch_filepath):
+        """Yields examples."""
+        # This method will receive as arguments the `gen_kwargs` defined in the previous `_split_generators` method.
+        # It is in charge of opening the given file and yielding (key, example) tuples from the dataset
+        # The key is not important, it's more here for legacy reason (legacy from tfds)
+        patch_examples = {}
+        if patch_filepath is not None:
+            with open(patch_filepath, encoding="utf-8") as f:
+                if self.config.label_variant == _REVISITED:
+                    patch_examples = {example["id"]: example for example in json.load(f)}
+                elif self.config.label_variant == _RETACRED:
+                    patch_examples = {_id: {"id": _id, "relation": label} for _id, label in json.load(f).items()}
+
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+            for example in data:
+                id_ = example["id"]
+
+                if id_ in patch_examples:
+                    example.update(patch_examples[id_])
+                elif self.config.label_variant == _RETACRED:
+                    # RE-TACRED was pruned, skip example if its id is not in patch_examples
+                    continue
+
+                yield id_, {
+                    "id": example["id"],
+                    "token": [convert_ptb_token(token) for token in example["token"]],
+                    "subj_start": example["subj_start"],
+                    "subj_end": example["subj_end"] + 1,  # make end offset exclusive
+                    "subj_type": example["subj_type"],
+                    "obj_start": example["obj_start"],
+                    "obj_end": example["obj_end"] + 1,  # make end offset exclusive
+                    "obj_type": example["obj_type"],
+                    "relation": example["relation"],
+                }
+