UCSG shallow parser

dc.contributor.author Kumar, Guntur Bharadwaja
dc.contributor.author Murthy, Kavi Narayana
dc.date.accessioned 2022-03-27T05:58:29Z
dc.date.available 2022-03-27T05:58:29Z
dc.date.issued 2006-07-07
dc.description.abstract Recently, there is an increasing interest in integrating rule based methods with statistical techniques for developing robust, wide coverage, high performance parsing systems. In this paper1, we describe an architecture, called UCSG shallow parser architecture, which combines linguistic constraints expressed in the form of finite state grammars with statistical rating using HMMs built from a POS-tagged corpus and an A* search for global optimization for determining the best shallow parse for a given sentence. The primary aim of the design of the UCSG parsing architecture is developing a judicious combination of linguistic and statistical methods to develop wide coverage robust shallow parsing systems, without the need for large scale manually parsed training corpora. The UCSG architecture uses a grammar to specify all valid structures and a statistical component to rate and rank the possible alternatives, so as to produce the best parse first without compromising on the ability to produce all possible parses. The architecture supports bootstrapping with an aim to reduce the need for parsed training corpora. The complete system has been implemented in Perl under Linux. In this paper we first describe the UCSG shallow parsing architecture and then focus on the evaluation of the UCSG finite state grammar for the chunking task for English. Recall of 91.16% and 93.73% have been obtained on the Susanne parsed corpus and CoNLL 2000 chunking task test data set respectively. Extensive experimentation is under way to evaluate the other modules. © Springer-Verlag Berlin Heidelberg 2006.
dc.identifier.citation Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). v.3878 LNCS
dc.identifier.issn 03029743
dc.identifier.uri 10.1007/11671299_18
dc.identifier.uri http://link.springer.com/10.1007/11671299_18
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8978
dc.subject A* search
dc.subject Chunking
dc.subject Finite State Grammar
dc.subject HMM
dc.subject Shallow Parsing
dc.subject UCSG Architecture
dc.title UCSG shallow parser
dc.type Book Series. Conference Paper
dspace.entity.type
Files
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: