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Program Systems: Theory and Applications, 2017, Volume 8, Issue 4, Pages 21–30 (Mi ps273)  

Artificial Intelligence, Intelligent Systems, Neural Networks

Automatic noun phrases extraction using preliminary segmentation and CRF with semantic features

N. A. Vlasova, A. V. Podobryaev

Ailamazyan Program Systems Institute of Russian Academy of Sciences

Abstract: We consider the task of finding the borders of noun phrases (NP) that are actants of predicates. First, we make a preliminary segmentation of sentences to fragments that contain NPs. Second, we use CRF to find the borders of NPs inside the fragments. Data from the knowledge base and information about named entities found in the text are used as features for machine learning. We present the results of our experiment and discuss future work. (in Russian).

Key words and phrases: shallow parsing, automatic information extraction, named entities, machine learning.

Funding Agency Grant Number
Russian Academy of Sciences - Federal Agency for Scientific Organizations 0077-2016-0002


DOI: https://doi.org/10.25209/2079-3316-2017-8-4-21-30

Full text: PDF file (756 kB)
References: PDF file   HTML file

UDC: 004.89:004.912
Received: 05.10.2017
Accepted: 01.11.2017

Citation: N. A. Vlasova, A. V. Podobryaev, “Automatic noun phrases extraction using preliminary segmentation and CRF with semantic features”, Program Systems: Theory and Applications, 8:4 (2017), 21–30

Citation in format AMSBIB
\Bibitem{VlaPod17}
\by N.~A.~Vlasova, A.~V.~Podobryaev
\paper Automatic noun phrases extraction using preliminary segmentation and CRF with semantic features
\jour Program Systems: Theory and Applications
\yr 2017
\vol 8
\issue 4
\pages 21--30
\mathnet{http://mi.mathnet.ru/ps273}
\crossref{https://doi.org/10.25209/2079-3316-2017-8-4-21-30}


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