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Towards Generalizable Place Name Recognition Systems: Analysis and Enhancement of NER Systems on English News from India

Authors:

Ali Hürriyetoğlu,

Çağri Yoltar,

Deniz YüretAuthors Info & Claims

GIR'18: Proceedings of the 12th Workshop on Geographic Information Retrieval

Article No.: 8, Pages 1 - 10

https://doi.org/10.1145/3281354.3281363

Published: 06 November 2018 Publication History

Abstract

Place name recognition is one of the key tasks in Information Extraction. In this paper, we tackle this task in English News from India. We first analyze the results obtained by using available tools and corpora and then train our own models to obtain better results. Most of the previous work done on entity recognition for English makes use of similar corpora for both training and testing. Yet we observe that the performance drops significantly when we test the models on different datasets. For this reason, we have trained various models using combinations of several corpora. Our results show that training models using combinations of several corpora improves the relative performance of these models but still more research on this area is necessary to obtain place name recognizers that generalize to any given dataset.

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Cited By

Hürriyetoğlu AYörük EYüret DYoltar ÇGürel BDuruşan FMutlu OAkdemir A(2019)Overview of CLEF 2019 Lab ProtestNews: Extracting Protests from News in a Cross-Context SettingExperimental IR Meets Multilinguality, Multimodality, and Interaction10.1007/978-3-030-28577-7_32(425-432)Online publication date: 3-Aug-2019
https://doi.org/10.1007/978-3-030-28577-7_32
Hürriyetoğlu AYörük EYüret DYoltar ÇGürel BDuruşan FMutlu O(2019)A Task Set Proposal for Automatic Protest Information Collection Across Multiple CountriesAdvances in Information Retrieval10.1007/978-3-030-15719-7_42(316-323)Online publication date: 14-Apr-2019
https://dl.acm.org/doi/10.1007/978-3-030-15719-7_42

Index Terms

Towards Generalizable Place Name Recognition Systems: Analysis and Enhancement of NER Systems on English News from India
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
  2. Machine learning
2. Information systems
  1. Information retrieval
    1. Evaluation of retrieval results
    2. Retrieval tasks and goals
      1. Information extraction

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cover image ACM Conferences

GIR'18: Proceedings of the 12th Workshop on Geographic Information Retrieval

November 2018

37 pages

ISBN:9781450360340

DOI:10.1145/3281354

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2018

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European Research Council

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SIGSPATIAL '18

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SIGSPATIAL

SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 6, 2018

WA, Seattle, USA

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GIR'18 Paper Acceptance Rate 8 of 12 submissions, 67%;

Overall Acceptance Rate 46 of 61 submissions, 75%

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Cited By

Hürriyetoğlu AYörük EYüret DYoltar ÇGürel BDuruşan FMutlu OAkdemir A(2019)Overview of CLEF 2019 Lab ProtestNews: Extracting Protests from News in a Cross-Context SettingExperimental IR Meets Multilinguality, Multimodality, and Interaction10.1007/978-3-030-28577-7_32(425-432)Online publication date: 3-Aug-2019
https://doi.org/10.1007/978-3-030-28577-7_32
Hürriyetoğlu AYörük EYüret DYoltar ÇGürel BDuruşan FMutlu O(2019)A Task Set Proposal for Automatic Protest Information Collection Across Multiple CountriesAdvances in Information Retrieval10.1007/978-3-030-15719-7_42(316-323)Online publication date: 14-Apr-2019
https://dl.acm.org/doi/10.1007/978-3-030-15719-7_42

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