AbstractIn this paper we explore different statistical dependency parsers for parsing Telugu. We consider five popular dependency parsers namely, MaltParser, MSTParser, TurboParser, ZPar and Easy-First Parser. We experiment with different parser and feature settings and show the impact of different settings. We also provide a detailed analysis of the performance of all the parsers on major dependency labels. We report our results on test data of Telugu dependency treebank provided in the ICON 2010 tools contest on Indian languages dependency parsing. We obtain state-of-the art performance of 91.8% in unlabeled attachment score and 70.0% in labeled attachment score. To the best of our knowledge ours is the only work which explored all the fi...
This paper describes and evaluates shal-low parsing of several Indian languages utilizing Conditiona...
In this paper, we present the preliminary experimentsof unsupervised dependency parsing on rawsegmen...
We present two dependency parsers for Persian, MaltParser and MSTParser, trained on theUppsala PErsi...
In this paper we explore different statistical dependency parsers for parsing Telugu. We consider fi...
AbstractIn this paper we explore different statistical dependency parsers for parsing Telugu. We con...
We report our dependency parsing experiments on two Indian Languages, Telugu and Hindi. We first exp...
In this paper, we describe the annotation and development of Telugu treebank following the Universal...
Key to fast adaptation of language technologies for any language hinges on the availability of funda...
This paper is an attempt to show that an inter-mediary level of analysis is an effective way for car...
Syntactic parsing is an important technique in the natural language processing, yet Latvian is still...
Abstract The paper describes a data driven dependency parsing approach which uses information about ...
This paper reports about our work in the ICON 2009 NLP TOOLS CONTEST: Parsing. We submitted two runs...
This paper presents the first dependency treebank for Bhojpuri, an Indo-Aryan language. Bhojpuri is ...
We present the first statistical dependency parsing results for Lithuanian, a morphologically rich l...
This paper presents an empirical comparison of different dependency parsers for Vietnamese, which ha...
This paper describes and evaluates shal-low parsing of several Indian languages utilizing Conditiona...
In this paper, we present the preliminary experimentsof unsupervised dependency parsing on rawsegmen...
We present two dependency parsers for Persian, MaltParser and MSTParser, trained on theUppsala PErsi...
In this paper we explore different statistical dependency parsers for parsing Telugu. We consider fi...
AbstractIn this paper we explore different statistical dependency parsers for parsing Telugu. We con...
We report our dependency parsing experiments on two Indian Languages, Telugu and Hindi. We first exp...
In this paper, we describe the annotation and development of Telugu treebank following the Universal...
Key to fast adaptation of language technologies for any language hinges on the availability of funda...
This paper is an attempt to show that an inter-mediary level of analysis is an effective way for car...
Syntactic parsing is an important technique in the natural language processing, yet Latvian is still...
Abstract The paper describes a data driven dependency parsing approach which uses information about ...
This paper reports about our work in the ICON 2009 NLP TOOLS CONTEST: Parsing. We submitted two runs...
This paper presents the first dependency treebank for Bhojpuri, an Indo-Aryan language. Bhojpuri is ...
We present the first statistical dependency parsing results for Lithuanian, a morphologically rich l...
This paper presents an empirical comparison of different dependency parsers for Vietnamese, which ha...
This paper describes and evaluates shal-low parsing of several Indian languages utilizing Conditiona...
In this paper, we present the preliminary experimentsof unsupervised dependency parsing on rawsegmen...
We present two dependency parsers for Persian, MaltParser and MSTParser, trained on theUppsala PErsi...