Summary of the paper

Title An Unsupervised Approach for Semantic Relation Interpretation
Authors Emiliano Giovannetti
Abstract In this work we propose a hybrid unsupervised approach for semantic relation extraction from Italian and English texts. The system takes as input pairs of ""distributionally similar"" terms, possibly involved in a semantic relation. To validate and label the anonymous relations holding between the terms in input, the candidate pairs of terms are looked for on the Web in the context of reliable lexico-syntactic patterns. This paper focuses on the definition of the patterns, on the measures used to assess the reliability of the suggested specific semantic relation and on the evaluation of the implemented system. So far, the system is able to extract the following types of semantic relations: hyponymy, meronymy, and co-hyponymy. The approach can however be easily extended to manage other relations by defining the appropriate battery of reliable lexico-syntactic patterns. Accuracy of the system was measured with scores of 83.3% for hyponymy, 75% for meronymy and 72.2% for co-hyponymy extraction.
Topics Information Extraction, Information Retrieval, Knowledge Discovery/Representation, Ontologies
Full paper An Unsupervised Approach for Semantic Relation Interpretation
Slides -
Bibtex @InProceedings{GIOVANNETTI10.734,
  author = {Emiliano Giovannetti},
  title = {An Unsupervised Approach for Semantic Relation Interpretation},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
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