Delete Multilingual-Opinion-Target-Extraction.py

Multilingual-Opinion-Target-Extraction.py

@@ -1,169 +0,0 @@
-# coding=utf-8
-# Copyright 2020 HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-"""Multilingual Opinion Target Extraction: A Parallel Corpus for Multilingual Opinion Extraction"""
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """\
-@inproceedings{garcia-ferrero-etal-2022-model,
-    title = "Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings",
-    author = "Garc{\'\i}a-Ferrero, Iker  and
-      Agerri, Rodrigo  and
-      Rigau, German",
-    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
-    month = dec,
-    year = "2022",
-    address = "Abu Dhabi, United Arab Emirates",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2022.findings-emnlp.478",
-    pages = "6403--6416",
-}
-"""
-
-_DESCRIPTION = """\
-SemEval-2016 Task 5: Aspect Based Sentiment Analysis data (https://alt.qcri.org/semeval2016/task5/) translated 
-into Spanish, French, Russian and Turkish using DeepL. The annotations have been manually
-projected from English to the target languages.
-"""
-
-_URL = "https://github.com/ikergarcia1996/Easy-Label-Projection/tree/main/data/absa_datasets/"
-
-
-class MOTEConfig(datasets.BuilderConfig):
-    """BuilderConfig for mOTE"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for mOTE.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(MOTEConfig, self).__init__(**kwargs)
-
-
-class MOTE(datasets.GeneratorBasedBuilder):
-    """MOTE dataset."""
-
-    BUILDER_CONFIGS = [
-        MOTEConfig(
-            name="en",
-            version=datasets.Version("1.0.0"),
-            description="MOTEConfig English dataset",
-        ),
-        MOTEConfig(
-            name="es",
-            version=datasets.Version("1.0.0"),
-            description="MOTEConfig Spanish dataset",
-        ),
-        MOTEConfig(
-            name="fr",
-            version=datasets.Version("1.0.0"),
-            description="MOTEConfig French dataset",
-        ),
-        MOTEConfig(
-            name="ru",
-            version=datasets.Version("1.0.0"),
-            description="MOTEConfig Russian dataset",
-        ),
-        MOTEConfig(
-            name="tr",
-            version=datasets.Version("1.0.0"),
-            description="MOTEConfig Turkish dataset",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "tokens": datasets.Sequence(datasets.Value("string")),
-                    "ner_tags": datasets.Sequence(
-                        datasets.features.ClassLabel(
-                            names=[
-                                "O",
-                                "B-TARGET",
-                                "I-TARGET",
-                            ]
-                        )
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://arxiv.org/abs/2210.12623",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        if self.config.name == "en":
-            urls_to_download = {
-                "train": f"{_URL}original/en/en.absa.train.tsv",
-                "test": f"{_URL}original/en/en.absa.test.tsv",
-            }
-        else:
-            urls_to_download = {
-                "train": f"{_URL}manual_projections/en2{self.config.name}/{self.config.name}.absa.train.tsv",
-                "test": f"{_URL}manual_projections/en2{self.config.name}/{self.config.name}.absa.test.tsv",
-            }
-
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": downloaded_files["train"]},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": downloaded_files["test"]},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        logger.info("⏳ Generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            guid = 0
-            tokens = []
-            ner_tags = []
-            for line in f:
-                line = line.strip()
-                if line == "" or line == "\n":
-                    if tokens:
-                        yield guid, {
-                            "id": str(guid),
-                            "tokens": tokens,
-                            "ner_tags": ner_tags,
-                        }
-                        guid += 1
-                        tokens = []
-                        ner_tags = []
-                else:
-                    splits = line.split()
-                    tokens.append(splits[0].strip())
-                    ner_tags.append(splits[1].strip())
-            # last example
-            if tokens:
-                yield guid, {
-                    "id": str(guid),
-                    "tokens": tokens,
-                    "ner_tags": ner_tags,
-                }