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Author: Atanas Chanev

Affiliation: Logical Factor Bulgaria, Bulgaria

Abstract: The methods of NLP and Cognitive Science can complement each other for the design of better models of the human sentence processing mechanism, on the one hand, and the development of better natural language parsers, on the other. In this paper, we show the performance of an automatic parser consistent with the architecture of the human parser of [2] on various human sentence processing experimental materials. Moreover, we use a linking hypothesis based on the concept of surprisal [9] to explain human reaction time patterns. Although our results are generally not consistent with the human performance, our emu- lations contribute to understanding the architecture of the human parser and its disambiguation strategies better. We also suggest that these strategies may possibly be used for improving the performance of automatic parsers.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Chanev, A. (2008). Emulation of Human Sentence Processing using an Automatic Dependency Shift-Reduce Parser. In Proceedings of the 5th International Workshop on Natural Language Processing and Cognitive Science (ICEIS 2008) - NLPCS; ISBN 978-989-8111-45-6, SciTePress, pages 137-146. DOI: 10.5220/0001732001370146

@conference{nlpcs08,
author={Atanas Chanev.},
title={Emulation of Human Sentence Processing using an Automatic Dependency Shift-Reduce Parser},
booktitle={Proceedings of the 5th International Workshop on Natural Language Processing and Cognitive Science (ICEIS 2008) - NLPCS},
year={2008},
pages={137-146},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001732001370146},
isbn={978-989-8111-45-6},
}

TY - CONF

JO - Proceedings of the 5th International Workshop on Natural Language Processing and Cognitive Science (ICEIS 2008) - NLPCS
TI - Emulation of Human Sentence Processing using an Automatic Dependency Shift-Reduce Parser
SN - 978-989-8111-45-6
AU - Chanev, A.
PY - 2008
SP - 137
EP - 146
DO - 10.5220/0001732001370146
PB - SciTePress