2019 Ivannikov Ispras Open Conference (ISPRAS)

Comparison of Named Entity Recognition Tools Applied to News Articles

Publication typeProceedings Article
Publication date2019-12-01
Abstract
Named Entity Recognition in texts is an important natural language processing task. There are many systems to solve this problem. These systems differ in targeting domains, processing methodologies, supported languages and recognized entity types. The presence of a large number of aspects creates difficulties for the user when choosing the appropriate tool for solving a specific problem. The aim of this work is a comparative study of seven publicly available and well-known libraries that can elicit named entities: Stanford NER, spaCy, NLTK, Polyglot, Flair, GATE and DeepPavlov. The article consists of seven sections. The introduction lists the areas of application for the Named Entity Recognition task and the approaches used to solve it. The second section is devoted to a review of works in which comparative studies of existing tools are presented. In the third section, the characteristics of the four text corpora that were used during the experiments are given. The fourth section contains a brief description of the tools selected for research. The fifth section describes the metrics used to evaluate tool performance. The sixth section presents the results of the experiments and their discussion. In conclusion the results of the work are summarized. The results of the study show that for the English language close values of the F1-score for the problem of Named Entities Recognition have the Flair and DeepPavlov libraries. For the Russian language the first place is taken by the DeepPavlov library, significantly surpassing other tools in quality.

Citations by journals

1
Natural Language Processing Journal
Natural Language Processing Journal, 1, 11.11%
Natural Language Processing Journal
1 publication, 11.11%
Lecture Notes in Computer Science
Lecture Notes in Computer Science, 1, 11.11%
Lecture Notes in Computer Science
1 publication, 11.11%
1

Citations by publishers

1
Elsevier
Elsevier, 1, 11.11%
Elsevier
1 publication, 11.11%
Springer Nature
Springer Nature, 1, 11.11%
Springer Nature
1 publication, 11.11%
1
  • We do not take into account publications that without a DOI.
  • Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
  • Statistics recalculated weekly.
Metrics
Share
Cite this
GOST |
Cite this
GOST Copy
Vychegzhanin S., Kotelnikov E. Comparison of Named Entity Recognition Tools Applied to News Articles // 2019 Ivannikov Ispras Open Conference (ISPRAS). 2019.
GOST all authors (up to 50) Copy
Vychegzhanin S., Kotelnikov E. Comparison of Named Entity Recognition Tools Applied to News Articles // 2019 Ivannikov Ispras Open Conference (ISPRAS). 2019.
RIS |
Cite this
RIS Copy
TY - CPAPER
DO - 10.1109/ISPRAS47671.2019.00017
UR - https://doi.org/10.1109%2FISPRAS47671.2019.00017
TI - Comparison of Named Entity Recognition Tools Applied to News Articles
T2 - 2019 Ivannikov Ispras Open Conference (ISPRAS)
AU - Vychegzhanin, Sergey
AU - Kotelnikov, Evgeny
PY - 2019
DA - 2019/12/01 00:00:00
ER -
BibTex
Cite this
BibTex Copy
@inproceedings{2019_Vychegzhanin,
author = {Sergey Vychegzhanin and Evgeny Kotelnikov},
title = {Comparison of Named Entity Recognition Tools Applied to News Articles},
year = {2019},
month = {dec}
}
Found error?