2006 EspressoAutoHarvestingSemanticRelations

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Subject Headings: Relation Mention Recognition Algorithm, Semi-Supervised Learning Algorithm, Espresso Algorithm.

Notes

Cited By

2007

Quotes

Abstract

In this paper, we present Espresso, a weakly-supervised, general-purpose, and accurate algorithm for harvesting semantic relations. The main contributions are: i) a method for exploiting generic patterns by filtering incorrect instances using the Web; and ii) a principled measure of pattern and instance reliability enabling the filtering algorithm. We present an empirical comparison of Espresso with various state of the art systems, on different size and genre corpora, on extracting various general and specific relations. Experimental results show that our exploitation of generic patterns substantially increases system recall with small effect on overall precision.


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2006 EspressoAutoHarvestingSemanticRelationsPatrick Pantel
Marco Pennacchiotti		Espresso: Leveraging Generic Patterns for Automatically Harvesting Semantic Relationshttp://acl.ldc.upenn.edu/P/P06/P06-1015.pdf
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