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