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# Inspec Benchmark Dataset for Keyphrase Generation |
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## About |
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Inspec is a dataset for benchmarking keyphrase extraction and generation models. |
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The dataset is composed of 2,000 abstracts of scientific papers collected from the [Inspec database](https://www.theiet.org/resources/inspec/). |
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Keyphrases were annotated by professional indexers in an uncontrolled setting (that is, not limited to thesaurus entries). |
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Details about the inspec dataset can be found in the original paper [(Hulth, 2003)][hulth-2003]. |
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Reference (indexer-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 [(Boudin and Gallina, 2021)][boudin-2021]. |
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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). |
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Stemming (Porter's stemmer implementation provided in `nltk`) is applied before reference keyphrases are matched against the source text. |
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Details about the process can be found in `prmu.py`. |
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## Content and statistics |
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The dataset is divided into the following three splits: |
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| Split | # documents | #words | # keyphrases | % Present | % Reordered | % Mixed | % Unseen | |
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| :--------- | ----------: | -----: | -----------: | --------: | ----------: | ------: | -------: | |
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| Train | 1,000 | 141.7 | 9.79 | 78.00 | 9.85 | 6.22 | 5.93 | |
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| Validation | 500 | 132.2 | 9.15 | 77.96 | 9.82 | 6.75 | 5.47 | |
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| Test | 500 | 134.8 | 9.83 | 78.70 | 9.92 | 6.48 | 4.91 | |
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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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- **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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## References |
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- (Hulth, 2003) Anette Hulth. 2003. |
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[Improved automatic keyword extraction given more linguistic knowledge](https://aclanthology.org/W03-1028). |
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In Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, pages 216-223. |
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- (Boudin and Gallina, 2021) 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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[hulth-2003]: https://aclanthology.org/W03-1028/ |
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[boudin-2021]: https://aclanthology.org/2021.naacl-main.330/ |
