Summary of the paper

Title Boosting Open Information Extraction with Noun-Based Relations
Authors Clarissa Xavier and Vera Lima
Abstract Open Information Extraction (Open IE) is a strategy for learning relations from texts, regardless the domain and without predefining these relations. Work in this area has focused mainly on verbal relations. In order to extend Open IE to extract relationships that are not expressed by verbs, we present a novel Open IE approach that extracts relations expressed in noun compounds (NCs), such as (oil, extracted from, olive) from “olive oil”, or in adjective-noun pairs (ANs), such as (moon, that is, gorgeous) from “gorgeous moon”. The approach consists of three steps: detection of NCs and ANs, interpretation of these compounds in view of corpus enrichment and extraction of relations from the enriched corpus. To confirm the feasibility of this method we created a prototype and evaluated the impact of the application of our proposal in two state-of-the-art Open IE extractors. Based on these tests we conclude that the proposed approach is an important step to fulfil the gap concerning the extraction of relations within the noun compounds and adjective-noun pairs in Open IE.
Full paper Boosting Open Information Extraction with Noun-Based Relations
Bibtex @InProceedings{XAVIER14.125,
  author = {Clarissa Xavier and Vera Lima},
  title = {Boosting Open Information Extraction with Noun-Based Relations},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
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