DocumentCode :
172490
Title :
Improving malt dependency parser using a simple grammar-driven unlexicalised dependency parser
Author :
Eragani, Anil Krishna ; Kuchibhotla, Varun
Author_Institution :
Language Technol. Res. Center, IIIT Hyderabad, Hyderabad, India
fYear :
2014
fDate :
20-22 Oct. 2014
Firstpage :
211
Lastpage :
214
Abstract :
In this paper, we present an approach to integrate unlexicalised grammatical features into Malt dependency parser. Malt parser is a lexicalised parser, and like every lexicalised parser, it is prone to data sparseness. We aim to address this problem by providing features from an unlexicalised parser. Contrary to lexicalised parsers, unlexicalised parsers are known for their robustness. We build a simple unlexicalised grammatical parser with POS tag sequences as grammar rules. We use the features from the grammatical parser as additional features to Malt. We achieved improvements of about 0.17-0.30% (UAS) on both English and Hindi state-of-the-art Malt results.
Keywords :
grammars; natural language processing; English state-of-the-art malt result; Hindi state-of-the-art malt result; POS tag sequences; data sparseness; grammar rules; grammar-driven unlexicalised dependency parser; malt dependency parser; unlexicalised grammatical features; unlexicalised grammatical parser; unlexicalised parsers; Data mining; Feature extraction; Grammar; Indexes; Robustness; Training; Training data; Malt Parser; syntactic parsing; unlexicalised grammar;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Asian Language Processing (IALP), 2014 International Conference on
Conference_Location :
Kuching
Type :
conf
DOI :
10.1109/IALP.2014.6973482
Filename :
6973482
Link To Document :
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