The Application of Constraint Rules to Data-driven Parsing

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Authors:
  • Sardar Jaf
  • Allan Ramsay

Abstract

In this paper, we show an approach to ex-
tracting different types of constraint rules
from a dependency treebank. Also, we
show an approach to integrating these con-
straint rules into a dependency data-driven
parser, where these constraint rules in-
form parsing decisions in specific situa-
tions where a set of parsing rule (which is
induced from a classifier) may recommend
several recommendations to the parser.
Our experiments have shown that parsing
accuracy could be improved by using dif-
ferent sets of constraint rules in combina-
tion with a set of parsing rules. Our parser
is based on the arc-standard algorithm of
MaltParser but with a number of exten-
sions, which we will discuss in some de-
tail.

Bibliographical metadata

Original languageEnglish
Title of host publication Proceedings of Recent Advances in Natural Language Processing
Subtitle of host publicationHissar, Bulgaria, Sep 7–9 2015
EditorsGalia Angelova, Kalina Bontcheva, Ruslan Mitkov
Pages232-238
Number of pages7
Publication statusPublished - 7 Sep 2015
EventRecent Advances in Natural Language Processing - Hissar, Bulgaria
Event duration: 7 Sep 20159 Sep 2015

Conference

ConferenceRecent Advances in Natural Language Processing
CityHissar, Bulgaria
Period7/09/159/09/15