This paper presents an ensemble system for dependency parsing: three parsers are separately trained and combined by means of a majority vote. The three parsers are (1) the MATE parser [http://code.google.com/p/mate-tools/], (2) the DeSR parser [http://sites.google.com/site/desrparser/], and (3) the MALT parser [http://maltparser.org/]. The MATE, that was never used before on Italian language, drastically outperforms the other parsers in the SPLeT shared task. Nonetheless, a simple voting combination further improves its performances

Simple parser combination

MAZZEI, Alessandro;BOSCO, CRISTINA
2012-01-01

Abstract

This paper presents an ensemble system for dependency parsing: three parsers are separately trained and combined by means of a majority vote. The three parsers are (1) the MATE parser [http://code.google.com/p/mate-tools/], (2) the DeSR parser [http://sites.google.com/site/desrparser/], and (3) the MALT parser [http://maltparser.org/]. The MATE, that was never used before on Italian language, drastically outperforms the other parsers in the SPLeT shared task. Nonetheless, a simple voting combination further improves its performances
2012
Semantic Processing of Legal Texts (SPLeT-2012)
istanbul, turchia
27 maggio 2012
Proceedings of Semantic Processing of Legal Texts (SPLeT-2012)
ELDA
65
69
9782951740877
http://www.lrec-conf.org/proceedings/lrec2012/workshops/27.LREC%202012%20Workshop%20Proceedings%20SPLeT.pdf
Alessandro MAZZEI; Cristina BOSCO
File in questo prodotto:
File Dimensione Formato  
MazzeiBoscoSPLET2012.pdf

Accesso aperto

Tipo di file: POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione 186.21 kB
Formato Adobe PDF
186.21 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/112811
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact