A corpus-based approach to discovering semantic relationships between named entities
Keywords:
corpus linguistics, discourse analysis, named entities, linguistic corpus, computational linguisticsAbstract
Introduction: The objective of this study is to analyze a news text related to cultural identity, which is part of a labeled
linguistic corpus, in order to annotate the syntactic and semantic relationships between the named entities in the text.
Materials and methods: A classification of the semantic relationships established between the named entities and how
they function in a labeled XML format is presented, using grammatical tagging and syntactic analysis. 20 named entities,
13 grammatical relationships, and 36 semantic relationships were tagged. Results: The proposal presented in this article
proves to be useful for developing and evaluating new open information extraction systems in Spanish. Discussion:
Linguistic corpora, corpus linguistics, and computational linguistics are valuable tools in the process of machine learning
for natural language understanding. The analysis of syntactic and semantic relationships between named entities in
a news text is crucial for relevant information extraction and linguistic pattern identification. Conclusion: This study
highlights the relevance of labeled linguistic corpora and corpus linguistics in the analysis of natural language and in the
development of natural language processing systems that are capable of understanding and analyzing human language
in different contexts. The importance of this work lies in the need to develop natural language processing systems that
enable computers to understand and analyze human language in different contexts.
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