WikiSplit++
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WikiSplit++: Easy Data Refinement for Split and Rephrase • 5 items • Updated • 1
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YAML Metadata Warning:The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
MinWikiSplit++
This dataset is the HuggingFace version of MinWikiSplit++.
MinWikiSplit++ enhances the original MinWikiSplit by applying two techniques: filtering through NLI classification and sentence-order reversing, which help to remove noise and reduce hallucinations compared to the original MinWikiSplit.
The preprocessed MinWikiSplit dataset that formed the basis for this can be found here.
Usage
import datasets as ds
dataset: ds.DatasetDict = ds.load_dataset("cl-nagoya/min-wikisplit-pp")
print(dataset)
# DatasetDict({
# train: Dataset({
# features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob'],
# num_rows: 139241
# })
# validation: Dataset({
# features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob'],
# num_rows: 17424
# })
# test: Dataset({
# features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob'],
# num_rows: 17412
# })
# })
Data Fields
- id: The ID of the data (note that it is not compatible with the existing MinWikiSplit)
- complex: A complex sentence
- simple_reversed: Simple sentences with their order reversed
- simple_tokenized: A list of simple sentences split by PySBD, not reversed in order
- simple_original: Simple sentences in their original order
- entailment_prob: The average probability that each simple sentence is classified as an entailment according to the complex sentence. DeBERTa-xxl is used for the NLI classification.
Paper
Tsukagoshi et al., WikiSplit++: Easy Data Refinement for Split and Rephrase, LREC-COLING 2024.
License
MinWikiSplit is build upon the WikiSplit dataset, which is distributed under the CC-BY-SA 4.0 license.
Therefore, this dataset follows suit and is distributed under the CC-BY-SA 4.0 license.
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