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--- |
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language: |
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- en |
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license: mit |
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size_categories: |
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- 10K<n<100K |
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pretty_name: Semantically-augmented FEVER for NLI |
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dataset_info: |
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features: |
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- name: id |
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dtype: string |
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- name: premise |
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dtype: string |
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- name: hypothesis |
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dtype: string |
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- name: label |
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dtype: string |
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- name: wsd |
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struct: |
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- name: premise |
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list: |
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- name: index |
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dtype: int64 |
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- name: text |
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dtype: string |
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- name: pos |
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dtype: string |
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- name: lemma |
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dtype: string |
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- name: bnSynsetId |
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dtype: string |
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- name: wnSynsetOffset |
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dtype: string |
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- name: nltkSynset |
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dtype: string |
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- name: hypothesis |
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list: |
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- name: index |
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dtype: int64 |
|
- name: text |
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dtype: string |
|
- name: pos |
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dtype: string |
|
- name: lemma |
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dtype: string |
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- name: bnSynsetId |
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dtype: string |
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- name: wnSynsetOffset |
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dtype: string |
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- name: nltkSynset |
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dtype: string |
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- name: srl |
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struct: |
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- name: premise |
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struct: |
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- name: tokens |
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list: |
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- name: index |
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dtype: int64 |
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- name: rawText |
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dtype: string |
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- name: annotations |
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list: |
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- name: tokenIndex |
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dtype: int64 |
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- name: verbatlas |
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struct: |
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- name: frameName |
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dtype: string |
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- name: roles |
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list: |
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- name: role |
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dtype: string |
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- name: score |
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dtype: float64 |
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- name: span |
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sequence: int64 |
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- name: englishPropbank |
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struct: |
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- name: frameName |
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dtype: string |
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- name: roles |
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list: |
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- name: role |
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dtype: string |
|
- name: score |
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dtype: float64 |
|
- name: span |
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sequence: int64 |
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- name: hypothesis |
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struct: |
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- name: tokens |
|
list: |
|
- name: index |
|
dtype: int64 |
|
- name: rawText |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: tokenIndex |
|
dtype: int64 |
|
- name: verbatlas |
|
struct: |
|
- name: frameName |
|
dtype: string |
|
- name: roles |
|
list: |
|
- name: role |
|
dtype: string |
|
- name: score |
|
dtype: float64 |
|
- name: span |
|
sequence: int64 |
|
- name: englishPropbank |
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struct: |
|
- name: frameName |
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dtype: string |
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- name: roles |
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list: |
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- name: role |
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dtype: string |
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- name: score |
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dtype: float64 |
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- name: span |
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sequence: int64 |
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splits: |
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- name: train |
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num_bytes: 357653267 |
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num_examples: 51086 |
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- name: validation |
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num_bytes: 15794078 |
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num_examples: 2288 |
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- name: test |
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num_bytes: 15736002 |
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num_examples: 2287 |
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download_size: 77623798 |
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dataset_size: 389183347 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: validation |
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path: data/validation-* |
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- split: test |
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path: data/test-* |
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--- |
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# Semantically-augmented FEVER for NLI |
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This dataset is a random downsample of the [FEVER dataset adapted for NLI](https://github.com/easonnie/combine-FEVER-NSMN/blob/master/other_resources/nli_fever.md). |
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We downsampled the training and development set to 25% of the original, and recovered labels for the development set from the original [FEVER dataset](https://huggingface.co/datasets/fever/fever). |
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The dataset is also augmented with semantic annotations such as Word Sense Disambiguation (WSD) and Semantic Role Labeling (SRL) information. |
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We annotated the whole downsampled dataset (both `premise` and `hypothesis`) with [AMuSE-WSD](https://aclanthology.org/2021.emnlp-demo.34) (Orlando et al., EMNLP 2021) and [InVeRo](https://aclanthology.org/2020.emnlp-demos.11) (Conia et al., EMNLP 2020). |
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## Dataset Creation |
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The idea was to curate a version of the FEVER dataset adapted to the NLI task for Homework 2 of the Multilingual Natural Language Processing 2024 course at Sapienza University of Rome. |
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We sourced the data following the instructions in [this repo](https://github.com/easonnie/combine-FEVER-NSMN/blob/master/other_resources/nli_fever.md), modifying the labels to the following schema: |
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```json |
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{ |
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"id": ..., # the FEVER dataset ID |
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"premise": ..., # the context in FEVER |
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"hypothesis": ..., # the query in FEVER |
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"label": ..., # mapped version of FEVER, where 'supports' -> 'entailment', 'refutes' -> 'contradiction' and 'not enough info' -> 'neutral' |
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} |
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``` |
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We filtered out any sample with an empty premise (a minority of the data) and downsampled both `train_fitems.jsonl` and `dev_fitems.jsonl` to 25% of their total size. |
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We then recovered the labels for the development set from the `labelled_dev` split in the [original FEVER](https://huggingface.co/datasets/fever/fever) and split the development set into the final `dev.jsonl` and `test.jsonl`. |
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Finally, we ran both AMuSE-WSD and InVeRo to augment our samples with WSD and SRL annotations, respectively. |
