Integrating special rules rooted in natural language semantics into the system of natural deduction

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Integrating special rules rooted in natural language semantics into the system of natural deduction

Popis výsledku v původním jazyce

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&apos;s sys-tem of natural deduction to answer questions in an &apos;intelligent&apos; way. It means that our system derives logical consequences entailed by the input sentences rather than merely searching answers by keywords. Natural lan-guage 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 presupposition 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.

Název v anglickém jazyce

Integrating special rules rooted in natural language semantics into the system of natural deduction

Popis výsledku anglicky

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&apos;s sys-tem of natural deduction to answer questions in an &apos;intelligent&apos; way. It means that our system derives logical consequences entailed by the input sentences rather than merely searching answers by keywords. Natural lan-guage 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 presupposition 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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence

ISBN

978-989-758-395-7

ISSN

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e-ISSN

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Počet stran výsledku

22

Strana od-do

410-421

Název nakladatele

SciTePress - Science and Technology Publications

Místo vydání

Setúbal

Místo konání akce

Valletta

Datum konání akce

22. 2. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000570767700045