Using the Web to Validate Lexico-Semantic Relations



The evaluation of semantic relations acquired automatically from text is a challenging task, which generally ends up being done by humans.
Despite less prone to errors, manual evaluation is hardly repeatable, time-consuming and sometimes subjective.
In this paper, we evaluate relational triples automatically, exploiting popular similarity measures on the Web.
After using these measures to quantify triples according to the co-occurrence of their arguments and textual patterns denoting their relation, some scores revealed to be highly correlated with the correction rate of the triples.
The measures were also used to select correct triples in a set, with best F1 scores around 96%.


Semantic relations, Natural Language Processing, Information Extraction, Information Retrieval


Natural Language Processing

Related Project



15th Portuguese Conference on Artificial Intelligence (EPIA 2011), Lisbon, Portugal, October 2011

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Year 2016 : 1 citations

 Petit, J. and Risch, J.-C. (2016). Identification de Relations Sémantiques Supportée par des Algorithmes d’Apprentissage Supervisé Utilisant des Mesures de Proximité Sémantique. In 16éme Conférence Internationale Francophone sur l'Extraction et la Gestion des Connaissances, EGC 2016, pages 73–84, Reims, France.