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--- |
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annotations_creators: |
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- unknown |
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language_creators: |
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- unknown |
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language: |
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- en |
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license: |
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- cc-by-nc-4.0 |
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multilinguality: |
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- monolingual |
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task_categories: |
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- text-mining |
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- text-generation |
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task_ids: |
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- keyphrase-generation |
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- keyphrase-extraction |
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size_categories: |
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- 100K<n<1M |
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pretty_name: KP-Biomed |
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--- |
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# KPBiomed, A Large-Scale Dataset for keyphrase generation |
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## About |
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This dataset is made of 5.6 million abstracts with author assigned keyphrases. |
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Details about the dataset can be found in the original paper: |
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Maël Houbre, Florian Boudin and Béatrice Daille. 2022. [A Large-Scale Dataset for Biomedical Keyphrase Generation](https://arxiv.org/abs/2211.12124). In Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI 2022). |
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Reference (author-assigned) keyphrases are also categorized under the PRMU (<u>P</u>resent-<u>R</u>eordered-<u>M</u>ixed-<u>U</u>nseen) scheme as proposed in the following paper: |
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- Florian Boudin and Ygor Gallina. 2021. |
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[Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness](https://aclanthology.org/2021.naacl-main.330/). |
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In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 4185–4193, Online. Association for Computational Linguistics. |
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Text pre-processing (tokenization) is carried out using spacy (en_core_web_sm model) with a special rule to avoid splitting words with hyphens (e.g. graph-based is kept as one token). Stemming (Porter's stemmer implementation provided in nltk) is applied before reference keyphrases are matched against the source text. |
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## Content |
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The details of the dataset are in the table below: |
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| Split | # documents | # keyphrases by document (average) | % Present | % Reordered | % Mixed | % Unseen | |
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| :----------- | ----------: | ---------------------------------: | --------: | ----------: | ------: | -------: | |
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| Train small | 500k | 5.24 | 66.31 | 7.16 | 12.60 | 13.93 | |
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| Train medium | 2M | 5.24 | 66.30 | 7.18 | 12.57 | 13.95 | |
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| Train large | 5.6M | 5.23 | 66.32 | 7.18 | 12.55 | 13.95 | |
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| Validation | 20k | 5.25 | 66.44 | 7.07 | 12.45 | 14.05 | |
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| Test | 20k | 5.22 | 66.59 | 7.22 | 12.44 | 13.75 | |
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The following data fields are available: |
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- **id**: unique identifier of the document. |
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- **title**: title of the document. |
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- **abstract**: abstract of the document. |
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- **keyphrases**: list of reference keyphrases. |
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- **mesh terms**: list of indexer assigned MeSH terms if available (around 68% of the articles) |
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- **prmu**: list of <u>P</u>resent-<u>R</u>eordered-<u>M</u>ixed-<u>U</u>nseen categories for reference keyphrases. |
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- **authors**: list of the article's authors |
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- **year**: publication year |
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**NB**: The present keyphrases (represented by the "P" label in the PRMU column) are sorted by their apparition order in the text (title + text). |
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