UNIMIB@NEEL-IT: Named Entity Recognition and Linking of Italian Tweets

Flavio Massimiliano Cecchini; Elisabetta Fersini; Pikakshi Manchanda; Enza Messina; Debora Nozza; Matteo Palmonari; Cezar Sas

doi:10.4000/books.aaccademia.1938

UNIMIB@NEEL-IT: Named Entity Recognition and Linking of Italian Tweets

Flavio Massimiliano Cecchini, Elisabetta Fersini, Pikakshi Manchanda, Enza Messina, Debora Nozza, Matteo Palmonari, Cezar Sas

Università Cattolica del Sacro Cuore

University of Milan - Bicocca

Risultato della ricerca: Contributo in libro › Contributo a convegno

Abstract

[Ita:]Questo articolo descrive il sistema proposto dal gruppo UNIMIB per il task di Named Entity Recognition and Linking applicato a tweet in lingua italiana (NEEL-IT). Il sistema, che rappresenta un approccio iniziale al problema, è costituito da tre passaggi fondamentali: (1) Named Entity Recognition tramite l’utilizzo di Conditional Random Fields, (2) Named Entity Linking considerando sia approcci supervisionati sia modelli di linguaggio basati su reti neurali, e (3) NIL clustering tramite un approccio basato su grafi.

Lingua originale	English
Titolo della pubblicazione ospite	EVALITA Evaluation of NLP and SPeech Tools for Italian - Proceedings of the Final Workshop
Pagine	54-59
Numero di pagine	6
Volume	1749
DOI	https://doi.org/10.4000/books.aaccademia.1938
Stato di pubblicazione	Pubblicato - 2016
Evento	International Workshop EVALITA - Naples, Italy Durata: 7 dic 2016 → 7 dic 2016

Convegno

Convegno	International Workshop EVALITA
Città	Naples, Italy
Periodo	7/12/16 → 7/12/16

Keywords

Entity Linking
Named Entity Recognition

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10.4000/books.aaccademia.1938

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@inproceedings{793feac3c66141bba6fbb8d44c8a031c,

title = "UNIMIB@NEEL-IT: Named Entity Recognition and Linking of Italian Tweets",

abstract = "This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian Tweets (NEEL-IT). The proposed pipeline, which represents an entry level system, is composed of three main steps: (1) Named Entity Recognition using Conditional Random Fields, (2) Named Entity Linking by considering both Supervised and Neural-Network Language models, and (3) NIL clustering byusing a graph-based approach.",

keywords = "Entity Linking, Named Entity Recognition, Entity Linking, Named Entity Recognition",

author = "Cecchini, {Flavio Massimiliano} and Elisabetta Fersini and Pikakshi Manchanda and Enza Messina and Debora Nozza and Matteo Palmonari and Cezar Sas",

year = "2016",

doi = "10.4000/books.aaccademia.1938",

language = "English",

isbn = "978-88-99982-09-6",

volume = "1749",

pages = "54--59",

booktitle = "EVALITA Evaluation of NLP and SPeech Tools for Italian - Proceedings of the Final Workshop",

note = "International Workshop EVALITA ; Conference date: 07-12-2016 Through 07-12-2016",

}

Cecchini, FM, Fersini, E, Manchanda, P, Messina, E, Nozza, D, Palmonari, M & Sas, C 2016, UNIMIB@NEEL-IT: Named Entity Recognition and Linking of Italian Tweets. in EVALITA Evaluation of NLP and SPeech Tools for Italian - Proceedings of the Final Workshop. vol. 1749, pagg. 54-59, International Workshop EVALITA, Naples, Italy, 7/12/16. https://doi.org/10.4000/books.aaccademia.1938

TY - GEN

T1 - UNIMIB@NEEL-IT: Named Entity Recognition and Linking of Italian Tweets

AU - Cecchini, Flavio Massimiliano

AU - Fersini, Elisabetta

AU - Manchanda, Pikakshi

AU - Messina, Enza

AU - Nozza, Debora

AU - Palmonari, Matteo

AU - Sas, Cezar

PY - 2016

Y1 - 2016

N2 - This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian Tweets (NEEL-IT). The proposed pipeline, which represents an entry level system, is composed of three main steps: (1) Named Entity Recognition using Conditional Random Fields, (2) Named Entity Linking by considering both Supervised and Neural-Network Language models, and (3) NIL clustering byusing a graph-based approach.

AB - This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian Tweets (NEEL-IT). The proposed pipeline, which represents an entry level system, is composed of three main steps: (1) Named Entity Recognition using Conditional Random Fields, (2) Named Entity Linking by considering both Supervised and Neural-Network Language models, and (3) NIL clustering byusing a graph-based approach.

KW - Entity Linking

KW - Named Entity Recognition

KW - Entity Linking

KW - Named Entity Recognition

UR - http://hdl.handle.net/10807/122102

U2 - 10.4000/books.aaccademia.1938

DO - 10.4000/books.aaccademia.1938

M3 - Conference contribution

SN - 978-88-99982-09-6

VL - 1749

SP - 54

EP - 59

BT - EVALITA Evaluation of NLP and SPeech Tools for Italian - Proceedings of the Final Workshop

T2 - International Workshop EVALITA

Y2 - 7 December 2016 through 7 December 2016

ER -

UNIMIB@NEEL-IT: Named Entity Recognition and Linking of Italian Tweets

Abstract

Convegno

Keywords

Accesso al documento

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