Increasing accuracy of a semantic word labelling tool based on a small lexicon

Hugo Sanjurjo-González


Abstract
Semantic annotation has become an important piece of information within corpus linguistics. This information is usually included for every lexical unit of the corpus providing a more exhaustive analysis of language. There are some resources such as lexicons or ontologies that allow this type of annotation. However, expanding these resources is a time-consuming task. This paper describes a simple NLP baseline for increasing accuracy of the existing semantic resources of the UCREL Semantic Analysis System (USAS). In our experiments, Spanish token accuracy is improved by up to 30% using this method.
Anthology ID:
2020.icon-main.2
Volume:
Proceedings of the 17th International Conference on Natural Language Processing (ICON)
Month:
December
Year:
2020
Address:
Indian Institute of Technology Patna, Patna, India
Editors:
Pushpak Bhattacharyya, Dipti Misra Sharma, Rajeev Sangal
Venue:
ICON
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
10–14
Language:
URL:
https://aclanthology.org/2020.icon-main.2
DOI:
Bibkey:
Cite (ACL):
Hugo Sanjurjo-González. 2020. Increasing accuracy of a semantic word labelling tool based on a small lexicon. In Proceedings of the 17th International Conference on Natural Language Processing (ICON), pages 10–14, Indian Institute of Technology Patna, Patna, India. NLP Association of India (NLPAI).
Cite (Informal):
Increasing accuracy of a semantic word labelling tool based on a small lexicon (Sanjurjo-González, ICON 2020)
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