There is a widely held belief in the natural lan-guage and computational linguistics commu-nities that Semantic Role Labeling (SRL) is a significant step toward improving important applications, e.g. question answering and in-formation extraction. In this paper, we present an SRL system for Modern Standard Arabic that exploits many aspects of the rich mor-phological features of the language. The ex-periments on the pilot Arabic Propbank data shows that our system based on Support Vec-tor Machines and Kernel Methods yields a global SRL F1 score of 82.17%, which im-proves the current state-of-the-art in Arabic SRL.
This paper presents work-in-progress investigating the development of a rule-based lexical frame-wor...
We describe a model for the lexical analy-sis of Arabic text, using the lists of alterna-tives suppl...
This paper presents a machine translation system (Hutchins 2003) called UniArab (Salem, Hensman and ...
In this paper, we present a system for Ara-bic semantic role labeling (SRL) based on SVMs and standa...
In this thesis, I examine the impact of morphological features on semantic role labeling (SRL) in Mo...
The natural language processing (NLP) community has recently experienced a growing interest in seman...
Abstract. We present a simple, two-steps supervised strategy for the identification and classificati...
In this paper we focus on the problem of question ranking in community question answering (cQA) foru...
The availability of large scale data sets of manually annotated predicate argument structures has re...
In this paper, we address the problem of processing Modern Standard Arabic. We present the second ge...
Applications of statistical Arabic NLP in general, and text mining in specific, along with the tools...
Treball de fi de màster en Lingüística Teòrica i AplicadaIn the last few years, there has been an in...
The study described in this paper belongs to the area of computational linguistics. Computational li...
This paper presents (AraSAS) the first open-source Arabic semantic analysis tagging system. AraSAS i...
This paper describes our contribution to the semantic role labeling task (SRL-only) of the CoNLL-200...
This paper presents work-in-progress investigating the development of a rule-based lexical frame-wor...
We describe a model for the lexical analy-sis of Arabic text, using the lists of alterna-tives suppl...
This paper presents a machine translation system (Hutchins 2003) called UniArab (Salem, Hensman and ...
In this paper, we present a system for Ara-bic semantic role labeling (SRL) based on SVMs and standa...
In this thesis, I examine the impact of morphological features on semantic role labeling (SRL) in Mo...
The natural language processing (NLP) community has recently experienced a growing interest in seman...
Abstract. We present a simple, two-steps supervised strategy for the identification and classificati...
In this paper we focus on the problem of question ranking in community question answering (cQA) foru...
The availability of large scale data sets of manually annotated predicate argument structures has re...
In this paper, we address the problem of processing Modern Standard Arabic. We present the second ge...
Applications of statistical Arabic NLP in general, and text mining in specific, along with the tools...
Treball de fi de màster en Lingüística Teòrica i AplicadaIn the last few years, there has been an in...
The study described in this paper belongs to the area of computational linguistics. Computational li...
This paper presents (AraSAS) the first open-source Arabic semantic analysis tagging system. AraSAS i...
This paper describes our contribution to the semantic role labeling task (SRL-only) of the CoNLL-200...
This paper presents work-in-progress investigating the development of a rule-based lexical frame-wor...
We describe a model for the lexical analy-sis of Arabic text, using the lists of alterna-tives suppl...
This paper presents a machine translation system (Hutchins 2003) called UniArab (Salem, Hensman and ...