@inproceedings{thuilier-danlos-2012-semantic,
title = "Semantic annotation of {F}rench corpora: animacy and verb semantic classes",
author = "Thuilier, Juliette and
Danlos, Laurence",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Do{\u{g}}an, Mehmet U{\u{g}}ur and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
month = may,
year = "2012",
address = "Istanbul, Turkey",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/552_Paper.pdf",
pages = "1533--1537",
abstract = "This paper presents a first corpus of French annotated for animacy and for verb semantic classes. The resource consists of 1,346 sentences extracted from three different corpora: the French Treebank (Abeill{\'e} and Barrier, 2004), the Est-R{\'e}publicain corpus (CNRTL) and the ESTER corpus (ELRA). It is a set of parsed sentences, containing a verbal head subcategorizing two complements, with annotations on the verb and on both complements, in the TIGER XML format (Mengel and Lezius, 2000). The resource was manually annotated and manually corrected by three annotators. Animacy has been annotated following the categories of Zaenen et al. (2004). Measures of inter-annotator agreement are good (Multi-pi = 0.82 and Multi-kappa = 0.86 (k = 3, N = 2360)). As for verb semantic classes, we used three of the five levels of classification of an existing dictionary: 'Les Verbes du Fran{\c{c}}ais' (Dubois and Dubois-Charlier, 1997). For the higher level (generic classes), the measures of agreement are Multi-pi = 0.84 and Multi-kappa = 0.87 (k = 3, N = 1346). The inter-annotator agreements show that the annotated data are reliable for both animacy and verbal semantic classes.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="thuilier-danlos-2012-semantic">
<titleInfo>
<title>Semantic annotation of French corpora: animacy and verb semantic classes</title>
</titleInfo>
<name type="personal">
<namePart type="given">Juliette</namePart>
<namePart type="family">Thuilier</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Laurence</namePart>
<namePart type="family">Danlos</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2012-05</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Nicoletta</namePart>
<namePart type="family">Calzolari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Khalid</namePart>
<namePart type="family">Choukri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Thierry</namePart>
<namePart type="family">Declerck</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mehmet</namePart>
<namePart type="given">Uğur</namePart>
<namePart type="family">Doğan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Bente</namePart>
<namePart type="family">Maegaard</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Joseph</namePart>
<namePart type="family">Mariani</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Asuncion</namePart>
<namePart type="family">Moreno</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jan</namePart>
<namePart type="family">Odijk</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Stelios</namePart>
<namePart type="family">Piperidis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>European Language Resources Association (ELRA)</publisher>
<place>
<placeTerm type="text">Istanbul, Turkey</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>This paper presents a first corpus of French annotated for animacy and for verb semantic classes. The resource consists of 1,346 sentences extracted from three different corpora: the French Treebank (Abeillé and Barrier, 2004), the Est-Républicain corpus (CNRTL) and the ESTER corpus (ELRA). It is a set of parsed sentences, containing a verbal head subcategorizing two complements, with annotations on the verb and on both complements, in the TIGER XML format (Mengel and Lezius, 2000). The resource was manually annotated and manually corrected by three annotators. Animacy has been annotated following the categories of Zaenen et al. (2004). Measures of inter-annotator agreement are good (Multi-pi = 0.82 and Multi-kappa = 0.86 (k = 3, N = 2360)). As for verb semantic classes, we used three of the five levels of classification of an existing dictionary: ’Les Verbes du Français’ (Dubois and Dubois-Charlier, 1997). For the higher level (generic classes), the measures of agreement are Multi-pi = 0.84 and Multi-kappa = 0.87 (k = 3, N = 1346). The inter-annotator agreements show that the annotated data are reliable for both animacy and verbal semantic classes.</abstract>
<identifier type="citekey">thuilier-danlos-2012-semantic</identifier>
<location>
<url>http://www.lrec-conf.org/proceedings/lrec2012/pdf/552_Paper.pdf</url>
</location>
<part>
<date>2012-05</date>
<extent unit="page">
<start>1533</start>
<end>1537</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Semantic annotation of French corpora: animacy and verb semantic classes
%A Thuilier, Juliette
%A Danlos, Laurence
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Doğan, Mehmet Uğur
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)
%D 2012
%8 May
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F thuilier-danlos-2012-semantic
%X This paper presents a first corpus of French annotated for animacy and for verb semantic classes. The resource consists of 1,346 sentences extracted from three different corpora: the French Treebank (Abeillé and Barrier, 2004), the Est-Républicain corpus (CNRTL) and the ESTER corpus (ELRA). It is a set of parsed sentences, containing a verbal head subcategorizing two complements, with annotations on the verb and on both complements, in the TIGER XML format (Mengel and Lezius, 2000). The resource was manually annotated and manually corrected by three annotators. Animacy has been annotated following the categories of Zaenen et al. (2004). Measures of inter-annotator agreement are good (Multi-pi = 0.82 and Multi-kappa = 0.86 (k = 3, N = 2360)). As for verb semantic classes, we used three of the five levels of classification of an existing dictionary: ’Les Verbes du Français’ (Dubois and Dubois-Charlier, 1997). For the higher level (generic classes), the measures of agreement are Multi-pi = 0.84 and Multi-kappa = 0.87 (k = 3, N = 1346). The inter-annotator agreements show that the annotated data are reliable for both animacy and verbal semantic classes.
%U http://www.lrec-conf.org/proceedings/lrec2012/pdf/552_Paper.pdf
%P 1533-1537
Markdown (Informal)
[Semantic annotation of French corpora: animacy and verb semantic classes](http://www.lrec-conf.org/proceedings/lrec2012/pdf/552_Paper.pdf) (Thuilier & Danlos, LREC 2012)
ACL