@inproceedings{colson-2020-extracting,
title = "Extracting meaning by idiomaticity: Description of the {HS}em{ID} system at {C}og{AL}ex {VI} (2020)",
author = "Colson, Jean-Pierre",
editor = "Zock, Michael and
Chersoni, Emmanuele and
Lenci, Alessandro and
Santus, Enrico",
booktitle = "Proceedings of the Workshop on the Cognitive Aspects of the Lexicon",
month = dec,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.cogalex-1.6",
pages = "54--58",
abstract = "The HSemID system, submitted to the CogALex VI Shared Task is a hybrid system relying mainly on metric clusters measured in large web corpora, complemented by a vector space model using cosine similarity to detect semantic associations. Although the system reached ra-ther weak results for the subcategories of synonyms, antonyms and hypernyms, with some dif-ferences from one language to another, it is able to measure general semantic associations (as being random or not-random) with an F1 score close to 0.80. The results strongly suggest that idiomatic constructions play a fundamental role in semantic associations. Further experiments are necessary in order to fine-tune the model to the subcategories of synonyms, antonyms, hy-pernyms and to explain surprising differences across languages. 1 Introduction",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="colson-2020-extracting">
<titleInfo>
<title>Extracting meaning by idiomaticity: Description of the HSemID system at CogALex VI (2020)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Jean-Pierre</namePart>
<namePart type="family">Colson</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2020-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Workshop on the Cognitive Aspects of the Lexicon</title>
</titleInfo>
<name type="personal">
<namePart type="given">Michael</namePart>
<namePart type="family">Zock</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Emmanuele</namePart>
<namePart type="family">Chersoni</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alessandro</namePart>
<namePart type="family">Lenci</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Enrico</namePart>
<namePart type="family">Santus</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Online</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>The HSemID system, submitted to the CogALex VI Shared Task is a hybrid system relying mainly on metric clusters measured in large web corpora, complemented by a vector space model using cosine similarity to detect semantic associations. Although the system reached ra-ther weak results for the subcategories of synonyms, antonyms and hypernyms, with some dif-ferences from one language to another, it is able to measure general semantic associations (as being random or not-random) with an F1 score close to 0.80. The results strongly suggest that idiomatic constructions play a fundamental role in semantic associations. Further experiments are necessary in order to fine-tune the model to the subcategories of synonyms, antonyms, hy-pernyms and to explain surprising differences across languages. 1 Introduction</abstract>
<identifier type="citekey">colson-2020-extracting</identifier>
<location>
<url>https://aclanthology.org/2020.cogalex-1.6</url>
</location>
<part>
<date>2020-12</date>
<extent unit="page">
<start>54</start>
<end>58</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Extracting meaning by idiomaticity: Description of the HSemID system at CogALex VI (2020)
%A Colson, Jean-Pierre
%Y Zock, Michael
%Y Chersoni, Emmanuele
%Y Lenci, Alessandro
%Y Santus, Enrico
%S Proceedings of the Workshop on the Cognitive Aspects of the Lexicon
%D 2020
%8 December
%I Association for Computational Linguistics
%C Online
%F colson-2020-extracting
%X The HSemID system, submitted to the CogALex VI Shared Task is a hybrid system relying mainly on metric clusters measured in large web corpora, complemented by a vector space model using cosine similarity to detect semantic associations. Although the system reached ra-ther weak results for the subcategories of synonyms, antonyms and hypernyms, with some dif-ferences from one language to another, it is able to measure general semantic associations (as being random or not-random) with an F1 score close to 0.80. The results strongly suggest that idiomatic constructions play a fundamental role in semantic associations. Further experiments are necessary in order to fine-tune the model to the subcategories of synonyms, antonyms, hy-pernyms and to explain surprising differences across languages. 1 Introduction
%U https://aclanthology.org/2020.cogalex-1.6
%P 54-58
Markdown (Informal)
[Extracting meaning by idiomaticity: Description of the HSemID system at CogALex VI (2020)](https://aclanthology.org/2020.cogalex-1.6) (Colson, CogALex 2020)
ACL