Linguistically–driven Selection of Correct Arcs for Dependency Parsing

Authors

  • Felice Dell’Orletta Istituto di Linguistica Computazionale “Antonio Zampolli” (ILC-CNR)
  • Giulia Venturi Istituto di Linguistica Computazionale “Antonio Zampolli” (ILC-CNR)
  • Simonetta Montemagni Istituto di Linguistica Computazionale “Antonio Zampolli” (ILC-CNR)

DOI:

https://doi.org/10.13053/cys-17-2-1517

Keywords:

Dependency parsing, correct arcs.

Abstract

LISCA is an unsupervised algorithm aimedat assigning a quality score to each arc generated bya dependency parser in order to produce a decreasingranking of arcs from correct to incorrect ones. LISCAexploits statistics about a set of linguistically–motivatedand dependency–based features extracted from a largecorpus of automatically parsed sentences and usesthem to assign a quality score to each arc of aparsed sentence belonging to the same domain ofthe automatically parsed corpus. LISCA has beensuccessfully tested on two datasets belonging to twodifferent domains and in all experiments it turned outto outperform different baselines, thus showing to beable to reliably detect correct arcs also representingdomain–specific peculiarities.

Author Biographies

Felice Dell’Orletta, Istituto di Linguistica Computazionale “Antonio Zampolli” (ILC-CNR)

Giulia Venturi, Istituto di Linguistica Computazionale “Antonio Zampolli” (ILC-CNR)

Simonetta Montemagni, Istituto di Linguistica Computazionale “Antonio Zampolli” (ILC-CNR)

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Published

2013-06-29

Issue

Vol. 17 No. 2 (2013): 17(2) April-June 2013

Section

Articles

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