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JOURNALS // Artificial Intelligence and Decision Making // Archive

Artificial Intelligence and Decision Making, 2020 Issue 1, Pages 17–26 (Mi iipr124)

This article is cited in 2 papers

Natural language processing

Extraction of script knowledge from texts. Part I. The task and the review of the state of the art

M. I. Suvorovaa, M. V. Kobozevaa, E. G. Sokolovab, S. Yu. Toldovab

a Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
b HSE University, Moscow, Russia

Abstract: This paper discusses the importance of automatic extraction of script knowledge for natural language understanding. We discuss theoretical approaches to the description of text structure: story grammars, scripts, frames and narrative schemas. We provide a list of research fields where automatic script knowledge extraction can be applied to achieve better precision and recall (e.g. automatic summarization, information extraction, coreference resolution, etc.). The article also presents popular approaches to the automatic extraction of script knowledge and methods for evaluation of such approaches. Besides, we present a list of datasets that can be used to train and test new models.

Keywords: script knowledge extraction, narrative schemas, scripts, frames, natural language processing.

DOI: 10.14357/20718594200102


 English version:
, 2021, 48:6, 517–523

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© Steklov Math. Inst. of RAS, 2024