Textual Entailment Recognition Based on Dependency Analysis and WordNet

The Recognizing Textual Entailment System shown here is based on the use of a broad-coverage parser to extract dependency relationships; in addition, WordNet relations are used to recognize entailment at the lexical level. The work investigates whether the mapping of dependency trees from text and hypothesis give better evidence of entailment than the matching of plain text alone. While the use of WordNet seems to improve system’s performance, the notion of mapping between trees here explored (inclusion) shows no improvement, suggesting that other notions of tree mappings should be explored such as tree edit distances or tree alignment distances.

• Type: Conference
• Year: 2005
• Where: MLCW
• Authors: Jesús Herrera, Anselmo Peñas, Felisa Verdejo
• Keywords: Entailment, Machine Learning, MLCW 2005, Textual Entailment System, Tree Edit Distances