Abstract
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 F 1 scores around 96%.
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Costa, H.P., Gonçalo Oliveira, H., Gomes, P. (2011). Using the Web to Validate Lexico-Semantic Relations. In: Antunes, L., Pinto, H.S. (eds) Progress in Artificial Intelligence. EPIA 2011. Lecture Notes in Computer Science(), vol 7026. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24769-9_43
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DOI: https://doi.org/10.1007/978-3-642-24769-9_43
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