Whole-part relations rule-based automatic identification: Issues from fine-grained error analysis

I. Markov, N. Mamede, J. Baptista

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

© Springer International Publishing Switzerland 2014.In this paper, we focus on the most frequent errors that occurred during the implementation of a rule-based module for semantic relations extraction, which has been integrated in STRING, a hybrid statistical and rule-based Natural Language Processing chain for Portuguese. We focus on whole-part relations (meronymy), that is, a semantic relation between an entity that is perceived as a constituent part of another entity, or a member of a set. In this case, we target the type of meronymy involving human entities and body-part nouns. We describe with some detail the decisions that were made in order to overcome the errors produced by the system and the solutions adopted to improve its performance.
Original languageEnglish
Pages (from-to)37-50
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8856
DOIs
Publication statusPublished - 2014
Externally publishedYes

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