This paper reports about our work in the ICON 2009 NLP TOOLS CONTEST: Parsing. We submitted two runs for Ben-gali. A statistical CRF based model fol-lowed by a rule-based post-processing technique has been used. The system has been trained on the NLP TOOLS CON-TEST: ICON 2009 datasets. The system demonstrated an unlabeled attachment score (UAS) of 74.09%, labeled attach-ment score (LAS) of 53.90 % and labeled accuracy score (LS) of 61.71 % respec-tively.
The paper introduces a dependency annotation effort which aims to fully annotate a million word Hind...
This work presents the development of the URDU.KON-TB treebank, its annotation evaluation & guidelin...
Kashmiri is a resource poor language with very less computational and language resources available f...
We report our dependency parsing experiments on two Indian Languages, Telugu and Hindi. We first exp...
Abstract The paper describes a data driven dependency parsing approach which uses information about ...
This paper is an attempt to show that an inter-mediary level of analysis is an effective way for car...
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...
The paper describes an approach to expedite the process of manual annotation of a Hindi dependency t...
Existing state of the art approaches for Sanskrit Dependency Parsing (SDP), are hybrid in nature, an...
In this paper, we present the preliminary experimentsof unsupervised dependency parsing on rawsegmen...
Key to fast adaptation of language technologies for any language hinges on the availability of funda...
Subcategorization information is a useful feature in dependency parsing. In this paper, we explore a...
This paper presents the first dependency treebank for Bhojpuri, an Indo-Aryan language. Bhojpuri is ...
Parsers are essential tools for several NLP applications. Here we introduce PassPort, a model for th...
The paper introduces a dependency annotation effort which aims to fully annotate a million word Hind...
This work presents the development of the URDU.KON-TB treebank, its annotation evaluation & guidelin...
Kashmiri is a resource poor language with very less computational and language resources available f...
We report our dependency parsing experiments on two Indian Languages, Telugu and Hindi. We first exp...
Abstract The paper describes a data driven dependency parsing approach which uses information about ...
This paper is an attempt to show that an inter-mediary level of analysis is an effective way for car...
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...
The paper describes an approach to expedite the process of manual annotation of a Hindi dependency t...
Existing state of the art approaches for Sanskrit Dependency Parsing (SDP), are hybrid in nature, an...
In this paper, we present the preliminary experimentsof unsupervised dependency parsing on rawsegmen...
Key to fast adaptation of language technologies for any language hinges on the availability of funda...
Subcategorization information is a useful feature in dependency parsing. In this paper, we explore a...
This paper presents the first dependency treebank for Bhojpuri, an Indo-Aryan language. Bhojpuri is ...
Parsers are essential tools for several NLP applications. Here we introduce PassPort, a model for th...
The paper introduces a dependency annotation effort which aims to fully annotate a million word Hind...
This work presents the development of the URDU.KON-TB treebank, its annotation evaluation & guidelin...
Kashmiri is a resource poor language with very less computational and language resources available f...