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ISC Publications

Publisher

Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)

Authors (5)

Paul McNamee
James C. Mayfield
Cash J. Costello
Caitlyn A. Bishop
Shelby K. Anderson
ISC Publications

2020

Tagging Location Phrases in Text

Abstract

For over 30 years researchers have studied the problem of automatically detecting named entities in written language. Throughout this time the majority of such work has focused on detection and classification of entities into coarse-grained types like: PERSON, ORGANIZATION, and LOCATION. Less attention has been focused on non-named mentions of entities, including non-named location phrases. In this work we describe the Location Phrase Detection task. Our key accomplishments include: developing a sequential tagging approach; crafting annotation guidelines; building an annotated dataset from news articles; and, conducting experiments in automated detection of location phrases with both statistical and neural taggers.

Citation

@inproceedingsmcnamee-etal-2020-tagging title: "Tagging Location Phrases in Text" author: "McNamee Paul and Mayfield James and Costello Cash and Bishop Caitlyn and Anderson Shelby" booktitle: "Proceedings of the 12th Language Resources and Evaluation Conference" month: may year: "2020" address: "Marseille France" publisher: "European Language Resources Association" url: "https://www.aclweb.org/anthology/2020.lrec-1.557" pages: "4521--4528" abstract: "For over thirty years researchers have studied the problem of automatically detecting named entities in written language. Throughout this time the majority of such work has focused on detection and classification of entities into coarse-grained types like: PERSON ORGANIZATION and LOCATION. Less attention has been focused on non-named mentions of entities including non-named location phrases such as ``the medical clinic in Telonge'' or ``2 km below the Dolin Maniche bridge''. In this work we describe the Location Phrase Detection task to identify such spans. Our key accomplishments include: developing a sequential tagging approach; crafting annotation guidelines; building annotated datasets for English and Russian news; and conducting experiments in automated detection of location phrases with both statistical and neural taggers. This work is motivated by extracting rich location information to support situational awareness during humanitarian crises such as natural disasters." language: "English" ISBN: "979-10-95546-34-4"

Citation

@inproceedingsmcnamee-etal-2020-tagging title: "Tagging Location Phrases in Text" author: "McNamee Paul and Mayfield James and Costello Cash and Bishop Caitlyn and Anderson Shelby" booktitle: "Proceedings of the 12th Language Resources and Evaluation Conference" month: may year: "2020" address: "Marseille France" publisher: "European Language Resources Association" url: "https://www.aclweb.org/anthology/2020.lrec-1.557" pages: "4521--4528" abstract: "For over thirty years researchers have studied the problem of automatically detecting named entities in written language. Throughout this time the majority of such work has focused on detection and classification of entities into coarse-grained types like: PERSON ORGANIZATION and LOCATION. Less attention has been focused on non-named mentions of entities including non-named location phrases such as ``the medical clinic in Telonge'' or ``2 km below the Dolin Maniche bridge''. In this work we describe the Location Phrase Detection task to identify such spans. Our key accomplishments include: developing a sequential tagging approach; crafting annotation guidelines; building annotated datasets for English and Russian news; and conducting experiments in automated detection of location phrases with both statistical and neural taggers. This work is motivated by extracting rich location information to support situational awareness during humanitarian crises such as natural disasters." language: "English" ISBN: "979-10-95546-34-4"