@inproceedings{touileb-etal-2018-automatic,
title = "Automatic identification of unknown names with specific roles",
author = "Touileb, Samia and
Pedersen, Truls and
Sj{\o}vaag, Helle",
editor = "Alex, Beatrice and
Degaetano-Ortlieb, Stefania and
Feldman, Anna and
Kazantseva, Anna and
Reiter, Nils and
Szpakowicz, Stan",
booktitle = "Proceedings of the Second Joint {SIGHUM} Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature",
month = aug,
year = "2018",
address = "Santa Fe, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-4517",
pages = "150--158",
abstract = "Automatically identifying persons in a particular role within a large corpus can be a difficult task, especially if you don{'}t know who you are actually looking for. Resources compiling names of persons can be available, but no exhaustive lists exist. However, such lists usually contain known names that are {``}visible{''} in the national public sphere, and tend to ignore the marginal and international ones. In this article we propose a method for automatically generating suggestions of names found in a corpus of Norwegian news articles, and which {``}naturally{''} belong to a given initial list of members, and that were not known (compiled in a list) beforehand. The approach is based, in part, on the assumption that surface level syntactic features reveal parts of the underlying semantic content and can help uncover the structure of the language.",
}
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<abstract>Automatically identifying persons in a particular role within a large corpus can be a difficult task, especially if you don’t know who you are actually looking for. Resources compiling names of persons can be available, but no exhaustive lists exist. However, such lists usually contain known names that are “visible” in the national public sphere, and tend to ignore the marginal and international ones. In this article we propose a method for automatically generating suggestions of names found in a corpus of Norwegian news articles, and which “naturally” belong to a given initial list of members, and that were not known (compiled in a list) beforehand. The approach is based, in part, on the assumption that surface level syntactic features reveal parts of the underlying semantic content and can help uncover the structure of the language.</abstract>
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%0 Conference Proceedings
%T Automatic identification of unknown names with specific roles
%A Touileb, Samia
%A Pedersen, Truls
%A Sjøvaag, Helle
%Y Alex, Beatrice
%Y Degaetano-Ortlieb, Stefania
%Y Feldman, Anna
%Y Kazantseva, Anna
%Y Reiter, Nils
%Y Szpakowicz, Stan
%S Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico
%F touileb-etal-2018-automatic
%X Automatically identifying persons in a particular role within a large corpus can be a difficult task, especially if you don’t know who you are actually looking for. Resources compiling names of persons can be available, but no exhaustive lists exist. However, such lists usually contain known names that are “visible” in the national public sphere, and tend to ignore the marginal and international ones. In this article we propose a method for automatically generating suggestions of names found in a corpus of Norwegian news articles, and which “naturally” belong to a given initial list of members, and that were not known (compiled in a list) beforehand. The approach is based, in part, on the assumption that surface level syntactic features reveal parts of the underlying semantic content and can help uncover the structure of the language.
%U https://aclanthology.org/W18-4517
%P 150-158
Markdown (Informal)
[Automatic identification of unknown names with specific roles](https://aclanthology.org/W18-4517) (Touileb et al., LaTeCH 2018)
ACL
- Samia Touileb, Truls Pedersen, and Helle Sjøvaag. 2018. Automatic identification of unknown names with specific roles. In Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 150–158, Santa Fe, New Mexico. Association for Computational Linguistics.