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@@ -45,3 +45,60 @@ configs:
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  - split: test
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  path: data/test-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - split: test
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  path: data/test-*
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  ---
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+
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+ # WikiSplit++
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+
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+ This dataset is the HuggingFace version of WikiSplit++.
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+ WikiSplit++ enhances the original WikiSplit by applying two techniques: filtering through NLI classification and sentence-order reversing, which help to remove noise and reduce hallucinations compared to the original WikiSplit.
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+ The preprocessed WikiSplit dataset that formed the basis for this can be found [here](https://huggingface.co/datasets/cl-nagoya/wikisplit).
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+
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+ ## Usage
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+
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+ ```python
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+ import datasets as ds
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+
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+ dataset: ds.DatasetDict = ds.load_dataset("cl-nagoya/wikisplit-pp", split="train")
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+
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+ print(dataset)
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+
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+ # DatasetDict({
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+ # train: Dataset({
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+ # features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob', 'split'],
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+ # num_rows: 504375
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+ # })
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+ # validation: Dataset({
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+ # features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob', 'split'],
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+ # num_rows: 63065
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+ # })
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+ # test: Dataset({
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+ # features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob', 'split'],
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+ # num_rows: 62993
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+ # })
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+ # })
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+ ```
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+
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+ ### Data Fields
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+
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+ - id: The ID of the data (note that it is not compatible with the existing WikiSplit)
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+ - complex: A complex sentence
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+ - simple_reversed: Simple sentences with their order reversed
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+ - simple_tokenized: A list of simple sentences split by [PySBD](https://github.com/nipunsadvilkar/pySBD), not reversed in order (often consists of 2 elements)
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+ - simple_original: Simple sentences in their original order
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+ - entailment_prob: The average probability that each simple sentence is classified as an entailment according to the complex sentence. [DeBERTa-xxl](https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli) is used for the NLI classification.
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+ - split: Indicates which split (train, val, or tune) this data belonged to in the original WikiSplit dataset
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+
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+ ## Paper
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+
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+ Tsukagoshi et al., [WikiSplit++: Easy Data Refinement for Split and Rephrase](https://arxiv.org/abs/2404.09002), LREC-COLING 2024.
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+
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+ ## Abstract
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+
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+ The task of Split and Rephrase, which splits a complex sentence into multiple simple sentences with the same meaning, improves readability and enhances the performance of downstream tasks in natural language processing (NLP).
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+ However, while Split and Rephrase can be improved using a text-to-text generation approach that applies encoder-decoder models fine-tuned with a large-scale dataset, it still suffers from hallucinations and under-splitting.
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+ To address these issues, this paper presents a simple and strong data refinement approach.
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+ Here, we create WikiSplit++ by removing instances in WikiSplit where complex sentences do not entail at least one of the simpler sentences and reversing the order of reference simple sentences.
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+ Experimental results show that training with WikiSplit++ leads to better performance than training with WikiSplit, even with fewer training instances.
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+ In particular, our approach yields significant gains in the number of splits and the entailment ratio, a proxy for measuring hallucinations.
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+
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+ ## License
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+