Negation and Speculation in NLP: A Survey, Corpora, Methods, and Applications
Mahany, Ahmed and Khaled, Heba and Elmitwally, Nouh and Aljohani, Naif and Ghoniemy, Said (2022) Negation and Speculation in NLP: A Survey, Corpora, Methods, and Applications. Applied Sciences, 12 (10). ISSN 2076-3417
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Abstract
Negation and speculation are universal linguistic phenomena that affect the performance of Natural Language Processing (NLP) applications, such as those for opinion mining and information retrieval, especially in biomedical data. In this article, we review the corpora annotated with negation and speculation in various natural languages and domains. Furthermore, we discuss the ongoing research into recent rule-based, supervised, and transfer learning techniques for the detection of negating and speculative content. Many English corpora for various domains are now annotated with negation and speculation; moreover, the availability of annotated corpora in other languages has started to increase. However, this growth is insufficient to address these important phenomena in languages with limited resources. The use of cross-lingual models and translation of the well-known languages are acceptable alternatives. We also highlight the lack of consistent annotation guidelines and the shortcomings of the existing techniques, and suggest alternatives that may speed up progress in this research direction. Adding more syntactic features may alleviate the limitations of the existing techniques, such as cue ambiguity and detecting the discontinuous scopes. In some NLP applications, inclusion of a system that is negation- and speculation-aware improves performance, yet this aspect is still not addressed or considered an essential step.
| Item Type: | Article | ||||||
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| Identification Number: | https://doi.org/10.3390/app12105209 | ||||||
| Dates: |
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| Uncontrolled Keywords: | negation; speculation; uncertainty; natural language processing; corpora annotation; annotation guidelines; rule-based algorithms; machine learning; deep learning | ||||||
| Subjects: | CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence |
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| Divisions: | Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology | ||||||
| Depositing User: | Nouh Elmitwally | ||||||
| Date Deposited: | 31 Aug 2022 14:31 | ||||||
| Last Modified: | 31 Aug 2022 14:31 | ||||||
| URI: | https://www.open-access.bcu.ac.uk/id/eprint/13504 |
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