Recognising textual entailment with logical inference
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
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My research path started with my master thesis (supervisor Prof. Stefania Costantini) about a neurobiologically-inspired proposal in the field of natural language processing. In more detail, we proposed the "Semantic Enhanced DCGs" (for short SE-DCGs) extension to the well-known DCG's to allow for parallel syntactic and semantic analysis, and generate semantically-based description of the sentence at hand. The analysis carried out through SE-DCG's was called "syntactic-semantic fully informed analysis", and it was designed to be as close as possible (at least in principle) to the results in the context of neuroscience that I had revised and studied. As proof-of-concept, I implemented the prototype of semantic search engine, the Mnemosine system. Mnemosine is able to interact with a user in natural language and to provide contextual answer at different levels of detail. Mnemosine has been applied to a practical case-study, i.e., to the WikiPedia Web pages. A brief overview of this work was presented during CICL 08 [1].