Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
sentiment-classification
Languages:
Polish
Size:
1K - 10K
License:
| import csv | |
| from typing import List, Generator, Tuple, Dict | |
| import datasets | |
| from datasets import DownloadManager | |
| from datasets.info import SupervisedKeysData | |
| _DESCRIPTION = """AspectEmo 1.0 dataset: Multi-Domain Corpus of Consumer Reviews for Aspect-Based | |
| Sentiment Analysis""" | |
| _CLASSES = ['O', | |
| 'B-a_plus_m', | |
| 'B-a_minus_m', | |
| 'B-a_zero', | |
| 'B-a_minus_s', | |
| 'B-a_plus_s', | |
| 'B-a_amb', | |
| 'B-a_minus_m:B-a_minus_m', | |
| 'B-a_minus_m:B-a_minus_m:B-a_minus_m', | |
| 'B-a_plus_m:B-a_plus_m', | |
| 'B-a_plus_m:B-a_plus_m:B-a_plus_m', | |
| 'B-a_zero:B-a_zero:B-a_zero', | |
| 'B-a_zero:B-a_zero', | |
| 'I-a_plus_m', | |
| 'B-a_zero:B-a_plus_m', | |
| 'B-a_minus_m:B-a_zero', | |
| 'B-a_minus_s:B-a_minus_s:B-a_minus_s', | |
| 'B-a_amb:B-a_amb', | |
| 'I-a_minus_m', | |
| 'B-a_minus_s:B-a_minus_s', | |
| 'B-a_plus_s:B-a_plus_s:B-a_plus_s', | |
| 'B-a_plus_m:B-a_plus_m:B-a_plus_m:B-a_plus_m:B-a_plus_m:B-a_plus_m', | |
| 'B-a_plus_m:B-a_amb', | |
| 'B-a_minus_m:B-a_plus_m', | |
| 'B-a_amb:B-a_amb:B-a_amb', | |
| 'I-a_zero', | |
| 'B-a_plus_s:B-a_plus_s', | |
| 'B-a_plus_m:B-a_plus_s', | |
| 'B-a_plus_m:B-a_zero', | |
| 'B-a_zero:B-a_zero:B-a_zero:B-a_zero:B-a_zero:B-a_zero', | |
| 'B-a_zero:B-a_minus_m', | |
| 'B-a_amb:B-a_plus_s', | |
| 'B-a_zero:B-a_minus_s'] | |
| _URLS = { | |
| "train": "https://huggingface.co/datasets/clarin-pl/aspectemo/resolve/main/data/train.tsv", | |
| "validation": "https://huggingface.co/datasets/clarin-pl/aspectemo/resolve/main/data/val.tsv", | |
| "test": "https://huggingface.co/datasets/clarin-pl/aspectemo/resolve/main/data/test.tsv", | |
| } | |
| class AspectEmo(datasets.GeneratorBasedBuilder): | |
| def _info(self) -> datasets.DatasetInfo: | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "orth": datasets.Sequence(datasets.Value("string")), | |
| "ctag": datasets.Sequence(datasets.Value("string")), | |
| "sentiment": datasets.Sequence(datasets.features.ClassLabel( | |
| names=_CLASSES, | |
| num_classes=len(_CLASSES) | |
| )), | |
| } | |
| ), | |
| supervised_keys=SupervisedKeysData(input="orth", output="sentiment"), | |
| homepage="https://clarin-pl.eu/dspace/handle/11321/849", | |
| ) | |
| def _split_generators(self, dl_manager: DownloadManager) -> List[datasets.SplitGenerator]: | |
| urls_to_download = _URLS | |
| 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.VALIDATION, | |
| gen_kwargs={"filepath": downloaded_files["validation"]}, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={"filepath": downloaded_files["test"]}, | |
| ), | |
| ] | |
| def _generate_examples( | |
| self, filepath: str | |
| ) -> Generator[Tuple[int, Dict[str, str]], None, None]: | |
| with open(filepath, "r", encoding="utf-8") as f: | |
| reader = csv.reader(f, delimiter="\t", quoting=csv.QUOTE_NONE) | |
| next(reader, None) # skip header | |
| id_, orth, ctag, sentiment = set(), [], [], [] | |
| for line in reader: | |
| if not line: | |
| assert len(id_) == 1 | |
| yield id_.pop(), {"orth": orth, "ctag": ctag, "sentiment": sentiment, } | |
| id_, orth, ctag, sentiment = set(), [], [], [] | |
| else: | |
| id_.add(line[0]) | |
| orth.append(line[1]) | |
| ctag.append(line[2]) | |
| sentiment.append(line[3]) | |