Combining relational and attributional similarity for semantic relation classification

Preslav Nakov, Zornitsa Kozareva

Research output: Contribution to journalConference article

8 Citations (Scopus)

Abstract

We combine relational and attributional similarity for the task of identifying instances of semantic relations, such as PRODUCT-PRODUCER and ORIGINENTITY, between nominals in text. We use no pre-existing lexical resources, thus simulating a realistic real-world situation, where the coverage of any such resource is limited. Instead, we mine the Web to automatically extract patterns (verbs, prepositions and coordinating conjunctions) expressing the relationship between the relation arguments, as well as hypernyms and co-hyponyms of the arguments, which we use in instance-based classifiers. The evaluation on the dataset of SemEval-1 Task 4 shows an improvement over the state-of-the-art for the case where using manually annotated WordNet senses is not allowed.

Original languageEnglish
Pages (from-to)323-330
Number of pages8
JournalInternational Conference Recent Advances in Natural Language Processing, RANLP
Publication statusPublished - 1 Dec 2011
Event8th International Conference on Recent Advances in Natural Language Processing, RANLP 2011 - Hissar, Bulgaria
Duration: 12 Sep 201114 Sep 2011

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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