In this paper, we explore how NLP can be used to automatically identify relevant syntactic complexity features in texts with the aim of assessing their correlation with specific linguistic registers. Our final goal is twofold. On the one hand, we demonstrate that automatic morpho-syntactic and syntactic annotation of texts provides sufficiently accurate output for use in the automatic extraction and measurement of syntactic complexity features. On the other hand, we identify the set of syntactic features strongly correlating with considered linguistic registers.

Towards an NLP-based approach for measuring syntactic complexity: preliminary experiments with Italian texts from different registers

Felice Dell'Orletta;Simonetta Montemagni
2011

Abstract

In this paper, we explore how NLP can be used to automatically identify relevant syntactic complexity features in texts with the aim of assessing their correlation with specific linguistic registers. Our final goal is twofold. On the one hand, we demonstrate that automatic morpho-syntactic and syntactic annotation of texts provides sufficiently accurate output for use in the automatic extraction and measurement of syntactic complexity features. On the other hand, we identify the set of syntactic features strongly correlating with considered linguistic registers.
Campo DC Valore Lingua
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC -
dc.authority.people Felice Dell'Orletta it
dc.authority.people Simonetta Montemagni it
dc.collection.id.s 33fc2b58-b895-438b-9d2a-2c5bc86a83a6 *
dc.collection.name 04.04 Presentazione/Comunicazione non pubblicata in atti di convegno *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 918 *
dc.date.accessioned 2024/02/21 05:57:10 -
dc.date.available 2024/02/21 05:57:10 -
dc.date.issued 2011 -
dc.description.abstracteng In this paper, we explore how NLP can be used to automatically identify relevant syntactic complexity features in texts with the aim of assessing their correlation with specific linguistic registers. Our final goal is twofold. On the one hand, we demonstrate that automatic morpho-syntactic and syntactic annotation of texts provides sufficiently accurate output for use in the automatic extraction and measurement of syntactic complexity features. On the other hand, we identify the set of syntactic features strongly correlating with considered linguistic registers. -
dc.description.affiliations CNR.ILC -
dc.description.allpeople Dell'Orletta, Felice; Montemagni, Simonetta -
dc.description.allpeopleoriginal Felice Dell'Orletta, Simonetta Montemagni -
dc.description.fulltext none en
dc.description.note ID_PUMA: cnr.ilc/2011-A3-001 -
dc.description.numberofauthors 2 -
dc.identifier.uri https://hdl.handle.net/20.500.14243/217961 -
dc.identifier.url http://www.benszm.net/BSBWWS/Dellorletta_Montemagni.pdf -
dc.language.iso eng -
dc.relation.conferencedate 29/10/2010 -
dc.relation.conferencename Workshop on "Cross-linguistic and language-internal variation in text and speech: focus on the joint analysis of multiple characteristics" -
dc.relation.conferenceplace Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg -
dc.subject.keywords Language Variation -
dc.subject.keywords Natural Language Processing -
dc.subject.keywords Syntactic Complexity -
dc.subject.singlekeyword Language Variation *
dc.subject.singlekeyword Natural Language Processing *
dc.subject.singlekeyword Syntactic Complexity *
dc.title Towards an NLP-based approach for measuring syntactic complexity: preliminary experiments with Italian texts from different registers en
dc.type.driver info:eu-repo/semantics/conferenceObject -
dc.type.full 04 Contributo in convegno::04.04 Presentazione/Comunicazione non pubblicata in atti di convegno it
dc.type.miur -2.0 -
dc.ugov.descaux1 205737 -
iris.orcid.lastModifiedDate 2024/04/04 20:51:18 *
iris.orcid.lastModifiedMillisecond 1712256678229 *
iris.sitodocente.maxattempts 2 -
Appare nelle tipologie: 04.04 Presentazione/Comunicazione non pubblicata (convegno, evento, webinar...)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/217961
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