Semantic Relation Classification: Task Formalisation and Refinement

Vivian Santos, Manuela Huerliman, Brian Davis, Siegfried Handschuh, André Freitas


Abstract
The identification of semantic relations between terms within texts is a fundamental task in Natural Language Processing which can support applications requiring a lightweight semantic interpretation model. Currently, semantic relation classification concentrates on relations which are evaluated over open-domain data. This work provides a critique on the set of abstract relations used for semantic relation classification with regard to their ability to express relationships between terms which are found in a domain-specific corpora. Based on this analysis, this work proposes an alternative semantic relation model based on reusing and extending the set of abstract relations present in the DOLCE ontology. The resulting set of relations is well grounded, allows to capture a wide range of relations and could thus be used as a foundation for automatic classification of semantic relations.
Anthology ID:
W16-5305
Volume:
Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Michael Zock, Alessandro Lenci, Stefan Evert
Venue:
CogALex
SIG:
SIGLEX
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
30–39
Language:
URL:
https://aclanthology.org/W16-5305
DOI:
Bibkey:
Cite (ACL):
Vivian Santos, Manuela Huerliman, Brian Davis, Siegfried Handschuh, and André Freitas. 2016. Semantic Relation Classification: Task Formalisation and Refinement. In Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V), pages 30–39, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Semantic Relation Classification: Task Formalisation and Refinement (Santos et al., CogALex 2016)
Copy Citation:
PDF:
https://aclanthology.org/W16-5305.pdf
Data
SemEval-2010 Task-8