Authors:
Marie Duží
and
Michal Fait
Affiliation:
VSB-Technical University of Ostrava, Department of Computer Science
Keyword(s):
Natural Language Processing, Question Answering, Natural Deduction, Transparent Intensional Logic - TIL, Anaphoric References, Property Modifiers, Factive Verbs.
Abstract:
The paper deals with natural language processing and question answering over large corpora of formalised natural language texts. Our background theory is the system of Transparent Intensional Logic (TIL). Having a fine-grained analysis of natural language sentences in the form of TIL constructions, we apply Gentzen’s system of natural deduction to answer questions in an ‘intelligent’ way. It means that our system derives logical consequences entailed by the input sentences rather than merely searching answers by keywords. Natural language semantics is rich, and plenty of its special features must be taken into account in the process of inferring answers. The TIL system makes it possible to formalise all these semantically salient features in a fine-grained way. In particular, since TIL is a logic of partial functions, it deals with non-referring terms and sentences with truth-value gaps in an appropriate way. This is important because sentences often come attached with a presuppositi
on that must be true in order that a given sentence had any truth-value. Yet, a problem arises how to integrate those special semantic rules into a standard deduction system. Proposal of the solution is one of the goals of this paper. The second novel result is this. There is a problem how to search relevant sentences in the labyrinth of input text data and how to vote for relevant applicable rules to meet the goal, i.e. to answer a given question. To this end, we propose a heuristic method driven by constituents of a given question.
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