Nominal Coreference Resolution Using Semantic Knowledge

1Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Coreference Resolution is a challenging task, considering the required linguistic knowledge and the sophistication of language processing techniques involved. Several other Natural Language Processing tasks may benefit from it, such as named entities recognition, relation extraction between named entities, summarization, sentiment analysis, among others. We propose a process for nominal coreference resolution in Portuguese, based on syntactic-semantic linguistic rules. Such rule models have been efficiently applied in other languages, such as: English, Spanish and Galician. They are useful when we deal with less resourceful languages, since the lack of sample-rich corpora may prevent accurate learning. We combine different levels of linguistic processing, using semantic relations as support, in order to infer referential relations between mentions. The proposed approach is the first model for Portuguese coreference resolution which uses semantic knowledge.

Cite

CITATION STYLE

APA

Fonseca, E., Vanin, A., & Vieira, R. (2018). Nominal Coreference Resolution Using Semantic Knowledge. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11122 LNAI, pp. 37–45). Springer Verlag. https://doi.org/10.1007/978-3-319-99722-3_4

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free