@inproceedings{roussel-2018-detecting,
title = "Detecting and Resolving Shell Nouns in {G}erman",
author = "Roussel, Adam",
editor = "Poesio, Massimo and
Ng, Vincent and
Ogrodniczuk, Maciej",
booktitle = "Proceedings of the First Workshop on Computational Models of Reference, Anaphora and Coreference",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-0707",
doi = "10.18653/v1/W18-0707",
pages = "61--67",
abstract = "This paper describes the design and evaluation of a system for the automatic detection and resolution of shell nouns in German. Shell nouns are general nouns, such as fact, question, or problem, whose full interpretation relies on a content phrase located elsewhere in a text, which these nouns simultaneously serve to characterize and encapsulate. To accomplish this, the system uses a series of lexico-syntactic patterns in order to extract shell noun candidates and their content in parallel. Each pattern has its own classifier, which makes the final decision as to whether or not a link is to be established and the shell noun resolved. Overall, about 26.2{\%} of the annotated shell noun instances were correctly identified by the system, and of these cases, about 72.5{\%} are assigned the correct content phrase. Though it remains difficult to identify shell noun instances reliably (recall is accordingly low in this regard), this system usually assigns the right content to correctly classified cases. cases.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="roussel-2018-detecting">
<titleInfo>
<title>Detecting and Resolving Shell Nouns in German</title>
</titleInfo>
<name type="personal">
<namePart type="given">Adam</namePart>
<namePart type="family">Roussel</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2018-06</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the First Workshop on Computational Models of Reference, Anaphora and Coreference</title>
</titleInfo>
<name type="personal">
<namePart type="given">Massimo</namePart>
<namePart type="family">Poesio</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vincent</namePart>
<namePart type="family">Ng</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Maciej</namePart>
<namePart type="family">Ogrodniczuk</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">New Orleans, Louisiana</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>This paper describes the design and evaluation of a system for the automatic detection and resolution of shell nouns in German. Shell nouns are general nouns, such as fact, question, or problem, whose full interpretation relies on a content phrase located elsewhere in a text, which these nouns simultaneously serve to characterize and encapsulate. To accomplish this, the system uses a series of lexico-syntactic patterns in order to extract shell noun candidates and their content in parallel. Each pattern has its own classifier, which makes the final decision as to whether or not a link is to be established and the shell noun resolved. Overall, about 26.2% of the annotated shell noun instances were correctly identified by the system, and of these cases, about 72.5% are assigned the correct content phrase. Though it remains difficult to identify shell noun instances reliably (recall is accordingly low in this regard), this system usually assigns the right content to correctly classified cases. cases.</abstract>
<identifier type="citekey">roussel-2018-detecting</identifier>
<identifier type="doi">10.18653/v1/W18-0707</identifier>
<location>
<url>https://aclanthology.org/W18-0707</url>
</location>
<part>
<date>2018-06</date>
<extent unit="page">
<start>61</start>
<end>67</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Detecting and Resolving Shell Nouns in German
%A Roussel, Adam
%Y Poesio, Massimo
%Y Ng, Vincent
%Y Ogrodniczuk, Maciej
%S Proceedings of the First Workshop on Computational Models of Reference, Anaphora and Coreference
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F roussel-2018-detecting
%X This paper describes the design and evaluation of a system for the automatic detection and resolution of shell nouns in German. Shell nouns are general nouns, such as fact, question, or problem, whose full interpretation relies on a content phrase located elsewhere in a text, which these nouns simultaneously serve to characterize and encapsulate. To accomplish this, the system uses a series of lexico-syntactic patterns in order to extract shell noun candidates and their content in parallel. Each pattern has its own classifier, which makes the final decision as to whether or not a link is to be established and the shell noun resolved. Overall, about 26.2% of the annotated shell noun instances were correctly identified by the system, and of these cases, about 72.5% are assigned the correct content phrase. Though it remains difficult to identify shell noun instances reliably (recall is accordingly low in this regard), this system usually assigns the right content to correctly classified cases. cases.
%R 10.18653/v1/W18-0707
%U https://aclanthology.org/W18-0707
%U https://doi.org/10.18653/v1/W18-0707
%P 61-67
Markdown (Informal)
[Detecting and Resolving Shell Nouns in German](https://aclanthology.org/W18-0707) (Roussel, CRAC 2018)
ACL
- Adam Roussel. 2018. Detecting and Resolving Shell Nouns in German. In Proceedings of the First Workshop on Computational Models of Reference, Anaphora and Coreference, pages 61–67, New Orleans, Louisiana. Association for Computational Linguistics.