Constituency Parsing of Bulgarian: Word- vs. Class-based Parsing

被引：0

作者：

Ghayoomi, Masood ^{[1
]}

Simov, Kiril ^{[2
]}

Osenova, Petya ^{[2
]}

机构：

[1] Free Univ Berlin, Dept Math & Comp Sci, Berlin, Germany

[2] IICT BAS, Linguist Modelling Dept, Sofia, Bulgaria

来源：

LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION | 2014年

关键词：

Constituency Parsing; Word Clustering; the Bulgarian Language; Treebanking;

D O I：

暂无

中图分类号：

H0 [语言学];

学科分类号：

030303 ; 0501 ; 050102 ;

摘要：

In this paper, we report the obtained results of two constituency parsers trained with BulTreeBank, an HPSG-based treebank for Bulgarian. To reduce the data sparsity problem, we propose using the Brown word clustering to do an off-line clustering and map the words in the treebank to create a class-based treebank. The observations show that when the classes outnumber the POS tags, the results are be. er. Since this approach adds on another dimension of abstraction (in comparison to the lemma), its coarse-grained representation can be used further for training statistical parsers.

引用

页码：4056 / 4060

页数：5

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