The Content Types Dataset: a New Resource to Explore Semantic and Functional Characteristics of Texts

Rachele Sprugnoli; Tommaso Caselli; Sara Tonelli; Giovanni Moretti

doi:10.18653/v1/e17-2042

The Content Types Dataset: a New Resource to Explore Semantic and Functional Characteristics of Texts

Rachele Sprugnoli^*, Tommaso Caselli, Sara Tonelli, Giovanni Moretti

^*Autore corrispondente per questo lavoro

Università Cattolica del Sacro Cuore

Risultato della ricerca: Contributo in libro › Contributo a convegno

1 Citazioni (Scopus)

Abstract

This paper presents a new resource, called Content Types Dataset, to promote the analysis of texts as a composition of units with specific semantic and functional roles. By developing this dataset, we also introduce a new NLP task for the automatic classification of Content Types. The annotation scheme and the dataset are described together with two sets of classification experiments.

Lingua originale	English
Titolo della pubblicazione ospite	Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
Pagine	260-266
Numero di pagine	7
Volume	2
DOI	https://doi.org/10.18653/v1/e17-2042
Stato di pubblicazione	Pubblicato - 2017
Evento	15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Valencia (Spagna) Durata: 3 apr 2017 → 7 apr 2017

Convegno

Convegno	15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017
Città	Valencia (Spagna)
Periodo	3/4/17 → 7/4/17

Keywords

semantics, computational linguistics, corpus annotation, information extraction

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10.18653/v1/e17-2042

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title = "The Content Types Dataset: a New Resource to Explore Semantic and Functional Characteristics of Texts",

abstract = "This paper presents a new resource, called Content Types Dataset, to promote the analysis of texts as a composition of units with specific semantic and functional roles. By developing this dataset, we also introduce a new NLP task for the automatic classification of Content Types. The annotation scheme and the dataset are described together with two sets of classification experiments.",

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author = "Rachele Sprugnoli and Tommaso Caselli and Sara Tonelli and Giovanni Moretti",

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booktitle = "Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers",

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Sprugnoli, R, Caselli, T, Tonelli, S & Moretti, G 2017, The Content Types Dataset: a New Resource to Explore Semantic and Functional Characteristics of Texts. in Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers. vol. 2, pagg. 260-266, 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, Valencia (Spagna), 3/4/17. https://doi.org/10.18653/v1/e17-2042

The Content Types Dataset: a New Resource to Explore Semantic and Functional Characteristics of Texts. / Sprugnoli, Rachele; Caselli, Tommaso; Tonelli, Sara et al.
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers. Vol. 2 2017. pag. 260-266.

Risultato della ricerca: Contributo in libro › Contributo a convegno

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T1 - The Content Types Dataset: a New Resource to Explore Semantic and Functional Characteristics of Texts

AU - Sprugnoli, Rachele

AU - Caselli, Tommaso

AU - Tonelli, Sara

AU - Moretti, Giovanni

PY - 2017

Y1 - 2017

N2 - This paper presents a new resource, called Content Types Dataset, to promote the analysis of texts as a composition of units with specific semantic and functional roles. By developing this dataset, we also introduce a new NLP task for the automatic classification of Content Types. The annotation scheme and the dataset are described together with two sets of classification experiments.

AB - This paper presents a new resource, called Content Types Dataset, to promote the analysis of texts as a composition of units with specific semantic and functional roles. By developing this dataset, we also introduce a new NLP task for the automatic classification of Content Types. The annotation scheme and the dataset are described together with two sets of classification experiments.

KW - semantics, computational linguistics, corpus annotation, information extraction

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DO - 10.18653/v1/e17-2042

M3 - Conference contribution

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EP - 266

BT - Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

T2 - 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017

Y2 - 3 April 2017 through 7 April 2017

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The Content Types Dataset: a New Resource to Explore Semantic and Functional Characteristics of Texts

Abstract

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Keywords

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