QuASIt: A cognitive inspired approach to question answering for the Italian language

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5 Citazioni (Scopus)

Abstract

In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt is both a rule-based and ontology-based question answering system. In the model, rules are aimed at understanding the query in terms of the linguistic typology of the question, and enabling its semantic processing as regards the search for the answer in the structured knowledge from DBPedia Italian project. Also the free explicative text in support of the query is analyzed if available. QuASIt attempts to answer for both multiple choice and essay questions. The model is presented, the implementation of the system is detailed, and some experiments are discussed.
Lingua originaleEnglish
Pagine464-476
Numero di pagine13
Stato di pubblicazionePublished - 2016

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Question Answering
Question Answering System
Linguistics
Query
Cognitive Architecture
Cognitive Models
Semantics
Natural Language
Ontology
Model
Term
Experiment
Knowledge
Language
Processing
Experiments

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cita questo

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title = "QuASIt: A cognitive inspired approach to question answering for the Italian language",
abstract = "In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt is both a rule-based and ontology-based question answering system. In the model, rules are aimed at understanding the query in terms of the linguistic typology of the question, and enabling its semantic processing as regards the search for the answer in the structured knowledge from DBPedia Italian project. Also the free explicative text in support of the query is analyzed if available. QuASIt attempts to answer for both multiple choice and essay questions. The model is presented, the implementation of the system is detailed, and some experiments are discussed.",
keywords = "Cognitive architecture, Computer Science (all), Linguistic typology, Question answering, Theoretical Computer Science",
author = "Roberto Pirrone and Arianna Pipitone and Giuseppe Tirone",
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T1 - QuASIt: A cognitive inspired approach to question answering for the Italian language

AU - Pirrone, Roberto

AU - Pipitone, Arianna

AU - Tirone, Giuseppe

PY - 2016

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N2 - In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt is both a rule-based and ontology-based question answering system. In the model, rules are aimed at understanding the query in terms of the linguistic typology of the question, and enabling its semantic processing as regards the search for the answer in the structured knowledge from DBPedia Italian project. Also the free explicative text in support of the query is analyzed if available. QuASIt attempts to answer for both multiple choice and essay questions. The model is presented, the implementation of the system is detailed, and some experiments are discussed.

AB - In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt is both a rule-based and ontology-based question answering system. In the model, rules are aimed at understanding the query in terms of the linguistic typology of the question, and enabling its semantic processing as regards the search for the answer in the structured knowledge from DBPedia Italian project. Also the free explicative text in support of the query is analyzed if available. QuASIt attempts to answer for both multiple choice and essay questions. The model is presented, the implementation of the system is detailed, and some experiments are discussed.

KW - Cognitive architecture

KW - Computer Science (all)

KW - Linguistic typology

KW - Question answering

KW - Theoretical Computer Science

UR - http://hdl.handle.net/10447/219973

UR - https://link.springer.com/chapter/10.1007%2F978-3-319-49130-1_34

M3 - Other

SP - 464

EP - 476

ER -