@inproceedings{same-van-deemter-2020-linguistic,
title = "A Linguistic Perspective on Reference: Choosing a Feature Set for Generating Referring Expressions in Context",
author = "Same, Fahime and
van Deemter, Kees",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.403",
doi = "10.18653/v1/2020.coling-main.403",
pages = "4575--4586",
abstract = "This paper reports on a structured evaluation of feature-based Machine Learning algorithms for selecting the form of a referring expression in discourse context. Based on this evaluation, we selected seven feature sets from the literature, amounting to 65 distinct linguistic features. The features were then grouped into 9 broad classes. After building Random Forest models, we used Feature Importance Ranking and Sequential Forward Search methods to assess the {``}importance{''} of the features. Combining the results of the two methods, we propose a consensus feature set. The 6 features in our consensus set come from 4 different classes, namely grammatical role, inherent features of the referent, antecedent form and recency.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="same-van-deemter-2020-linguistic">
<titleInfo>
<title>A Linguistic Perspective on Reference: Choosing a Feature Set for Generating Referring Expressions in Context</title>
</titleInfo>
<name type="personal">
<namePart type="given">Fahime</namePart>
<namePart type="family">Same</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kees</namePart>
<namePart type="family">van Deemter</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2020-dec</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 28th International Conference on Computational Linguistics</title>
</titleInfo>
<originInfo>
<publisher>International Committee on Computational Linguistics</publisher>
<place>
<placeTerm type="text">Barcelona, Spain (Online)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>This paper reports on a structured evaluation of feature-based Machine Learning algorithms for selecting the form of a referring expression in discourse context. Based on this evaluation, we selected seven feature sets from the literature, amounting to 65 distinct linguistic features. The features were then grouped into 9 broad classes. After building Random Forest models, we used Feature Importance Ranking and Sequential Forward Search methods to assess the “importance” of the features. Combining the results of the two methods, we propose a consensus feature set. The 6 features in our consensus set come from 4 different classes, namely grammatical role, inherent features of the referent, antecedent form and recency.</abstract>
<identifier type="citekey">same-van-deemter-2020-linguistic</identifier>
<identifier type="doi">10.18653/v1/2020.coling-main.403</identifier>
<location>
<url>https://aclanthology.org/2020.coling-main.403</url>
</location>
<part>
<date>2020-dec</date>
<extent unit="page">
<start>4575</start>
<end>4586</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T A Linguistic Perspective on Reference: Choosing a Feature Set for Generating Referring Expressions in Context
%A Same, Fahime
%A van Deemter, Kees
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 dec
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F same-van-deemter-2020-linguistic
%X This paper reports on a structured evaluation of feature-based Machine Learning algorithms for selecting the form of a referring expression in discourse context. Based on this evaluation, we selected seven feature sets from the literature, amounting to 65 distinct linguistic features. The features were then grouped into 9 broad classes. After building Random Forest models, we used Feature Importance Ranking and Sequential Forward Search methods to assess the “importance” of the features. Combining the results of the two methods, we propose a consensus feature set. The 6 features in our consensus set come from 4 different classes, namely grammatical role, inherent features of the referent, antecedent form and recency.
%R 10.18653/v1/2020.coling-main.403
%U https://aclanthology.org/2020.coling-main.403
%U https://doi.org/10.18653/v1/2020.coling-main.403
%P 4575-4586
Markdown (Informal)
[A Linguistic Perspective on Reference: Choosing a Feature Set for Generating Referring Expressions in Context](https://aclanthology.org/2020.coling-main.403) (Same & van Deemter, COLING 2020)
ACL