Initial Commit

.gitattributes

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README.md

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+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- machine-generated
+languages:
+- fr
+- fr-FR
+licenses:
+- wtfpl
+multilinguality:
+- monolingual
+pretty_name: French Wikipedia dataset for Entity Linking
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- token-classification
+task_ids: []
+---
+
+# Dataset Card for frwiki_good_pages_el
+
+## Dataset Description
+
+- Repository: [frwiki_el](https://github.com/GaaH/frwiki_el)
+- Point of Contact: [Gaëtan Caillaut](mailto://g.caillaut@brgm.fr)
+
+### Dataset Summary
+
+This dataset contains articles from the French Wikipédia.
+It is intended to be used to train Entity Linking (EL) systems. Links in articles are used to detect named entities.
+
+The dataset `frwiki` contains sentences of each Wikipedia pages.
+
+The dataset `entities` contains description for each Wikipedia pages.
+
+### Languages
+
+- French
+
+## Dataset Structure
+
+### frwiki
+
+```
+{
+    "name": "Title of the page",
+    "wikidata_id": "Identifier of the related Wikidata entity. Can be null.",
+    "wikipedia_id": "Identifier of the Wikipedia page",
+    "wikipedia_url": "URL to the Wikipedia page",
+    "wikidata_url": "URL to the Wikidata page. Can be null.",
+    "words": ["words", "in", "the", "sentence"],
+    "ner": ["ner", "labels", "of", "each", "words"],
+    "el": ["el", "labels", "of", "each", "words"]
+}
+```
+
+### entities
+
+```
+{
+    "name": "Title of the page",
+    "wikidata_id": "Identifier of the related Wikidata entity. Can be null.",
+    "wikipedia_id": "Identifier of the Wikipedia page",
+    "wikipedia_url": "URL to the Wikipedia page",
+    "wikidata_url": "URL to the Wikidata page. Can be null.",
+    "description": "Description of the entity"
+}
+```

data/corpus.jsonl.gz

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+size 3047426604

data/entities.jsonl.gz

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+oid sha256:0e6cc15e381b296240ea825e1d49d072d6ec61e0395ddf9786bfaf4f2a4dbfb6
+size 238584221

frwiki_el.py

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+# 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.
+"""TODO: Add a description here."""
+
+
+import re
+import gzip
+import json
+import datasets
+from pathlib import Path
+
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = ""
+
+_DESCRIPTION = """\
+French Wikipedia dataset for Entity Linking
+"""
+
+_HOMEPAGE = "https://github.com/GaaH/frwiki_el"
+
+_LICENSE = "WTFPL"
+
+_URLs = {
+    "frwiki": "data/corpus.jsonl.gz",
+    "entities": "data/entities.jsonl.gz",
+}
+
+_NER_CLASS_LABELS = [
+    "B",
+    "I",
+    "O",
+]
+
+_ENTITY_TYPES = [
+    "DATE",
+    "PERSON",
+    "GEOLOC",
+    "ORG",
+    "OTHER",
+]
+
+
+def item_to_el_features(item, title2qid):
+    res = {
+        "title": item['name'].replace("_", " "),
+        "wikidata_id": item['wikidata_id'],
+        "wikipedia_id": item['wikipedia_id'],
+        "wikidata_url": item['wikidata_url'],
+        "wikipedia_url": item['wikipedia_url'],
+    }
+    text_dict = {
+        "words": [],
+        "ner": [],
+        "el": [],
+    }
+    entity_pattern = r"\[E=(.+?)\](.+?)\[/E\]"
+
+    # start index of the previous text
+    i = 0
+    text = item['text']
+    for m in re.finditer(entity_pattern, text):
+        mention_title = m.group(1)
+        mention = m.group(2)
+
+        mention_qid = title2qid.get(mention_title.replace("_", " "), "unknown")
+
+        mention_words = mention.split()
+
+        j = m.start(0)
+        prev_text = text[i:j].split()
+        len_prev_text = len(prev_text)
+        text_dict["words"].extend(prev_text)
+        text_dict["ner"].extend(["O"] * len_prev_text)
+        text_dict["el"].extend([None] * len_prev_text)
+
+        text_dict["words"].extend(mention_words)
+
+        len_mention_tail = len(mention_words) - 1
+        text_dict["ner"].extend(["B"] + ["I"] * len_mention_tail)
+        text_dict["el"].extend([mention_qid] + [mention_qid] * len_mention_tail)
+
+        i = m.end(0)
+
+    tail = text[i:].split()
+    len_tail = len(tail)
+    text_dict["words"].extend(tail)
+    text_dict["ner"].extend(["O"] * len_tail)
+    text_dict["el"].extend([None] * len_tail)
+    res.update(text_dict)
+    return res
+
+
+class FrwikiElDataset(datasets.GeneratorBasedBuilder):
+    """
+    """
+
+    VERSION = datasets.Version("0.1.0")
+
+    # This is an example of a dataset with multiple configurations.
+    # If you don't want/need to define several sub-sets in your dataset,
+    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+    # If you need to make complex sub-parts in the datasets with configurable options
+    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+    # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'second_domain')
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="frwiki", version=VERSION,
+                               description="The frwiki dataset for Entity Linking"),
+        datasets.BuilderConfig(name="entities", version=VERSION,
+                               description="Entities and their descriptions"),
+    ]
+
+    # It's not mandatory to have a default configuration. Just use one if it make sense.
+    DEFAULT_CONFIG_NAME = "frwiki"
+
+    def _info(self):
+        if self.config.name == "frwiki":
+            features = datasets.Features({
+                "name": datasets.Value("string"),
+                "wikidata_id": datasets.Value("string"),
+                "wikipedia_id": datasets.Value("string"),
+                "wikipedia_url": datasets.Value("string"),
+                "wikidata_url": datasets.Value("string"),
+                "words": [datasets.Value("string")],
+                "ner": [datasets.ClassLabel(names=_NER_CLASS_LABELS)],
+                "el": [datasets.Value("string")],
+            })
+        elif self.config.name == "entities":
+            features = datasets.Features({
+                "name": datasets.Value("string"),
+                "wikidata_id": datasets.Value("string"),
+                "wikipedia_id": datasets.Value("string"),
+                "wikipedia_url": datasets.Value("string"),
+                "wikidata_url": datasets.Value("string"),
+                "description": datasets.Value("string"),
+            })
+
+        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
+            # Here we define them above because they are different between the two configurations
+            features=features,
+            # 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."""
+        # 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
+        filepath = _URLs[self.config.name]
+        # data_dir = dl_manager.download_and_extract(my_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "path": filepath,
+                }
+            )
+        ]
+
+    def _generate_examples(self, path):
+        """ 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.
+
+        # entities_path = Path(data_dir, "entities.jsonl.gz")
+        # corpus_path = Path(data_dir, "corpus.jsonl.gz")
+
+        def _identiy(x):
+            return x
+
+        with gzip.open(path, "rt", encoding="UTF-8") as crps_file:
+            for id, line in enumerate(crps_file):
+                item = json.loads(line, parse_int=_identiy, parse_float=_identiy, parse_constant=_identiy)
+                yield id, item