TAILIEUCHUNG - Báo cáo khoa học: "Unsupervised Induction of Modern Standard Arabic Verb Classes Using Syntactic Frames and LSA"

We exploit the resources in the Arabic Treebank (ATB) and Arabic Gigaword (AG) to determine the best features for the novel task of automatically creating lexical semantic verb classes for Modern Standard Arabic (MSA). The verbs are classified into groups that share semantic elements of meaning as they exhibit similar syntactic behavior. The results of the clustering experiments are compared with a gold standard set of classes, which is approximated by using the noisy English translations provided in the ATB to create Levin-like classes for MSA. The quality of the clusters is found to be sensitive to the inclusion. | Unsupervised Induction of Modern Standard Arabic Verb Classes Using Syntactic Frames and LSA Neal Snider Linguistics Department Stanford University Stanford CA 94305 snider@ Mona Diab Center for Computational Learning Systems Columbia University New York NY 10115 mdiab@ Abstract We exploit the resources in the Arabic Treebank ATB and Arabic Gigaword AG to determine the best features for the novel task of automatically creating lexical semantic verb classes for Modern Standard Arabic MSA . The verbs are classified into groups that share semantic elements of meaning as they exhibit similar syntactic behavior. The results of the clustering experiments are compared with a gold standard set of classes which is approximated by using the noisy English translations provided in the ATB to create Levin-like classes for MSA. The quality of the clusters is found to be sensitive to the inclusion of syntactic frames LSA vectors morphological pattern and subject animacy. The best set of parameters yields an Fạ 1 score of compared to a random baseline of an Fs i score of . 1 Introduction The creation of the Arabic Treebank ATB and Arabic Gigaword AG facilitates corpus based studies of many interesting linguistic phenomena in Modern Standard Arabic MSA .1 The ATB comprises manually annotated morphological and syntactic analyses of newswire text from different Arabic sources while the AG is simply a huge collection of raw Arabic newswire text. In our ongoing project we exploit the ATB and AG to determine the best features for the novel task of automatically creating lexical semantic verb classes 1http for MSA. We are interested in the problem of classifying verbs in MSA into groups that share semantic elements of meaning as they exhibit similar syntactic behavior. This manner of classifying verbs in a language is mainly advocated by Levin 1993 . The Levin Hypothesis LH contends that verbs that exhibit similar syntactic behavior

• Báo cáo khoa học
• Unsupervised Induction
• Modern Standard Arabic Verb Classes
• Syntactic Frames and LSA
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Unsupervised Semantic Role Induction
• Global Role Ordering
• Nikhil Garg
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• Unsupervised Ontology Induction from Text
• Hoifung Poon
• Pedro Domingos
• Improved Unsupervised POS Induction
• Prototype Discovery
• Omri Abend
• Simple Unsupervised Grammar Induction
• Raw Text
• Cascaded Finite State Models
• Split Merge Clustering
• Joel Lang
• Unsupervised Multilingual Grammar Induction
• Benjamin Snyder
• Tahira Naseem
• A Hierarchical Pitman Yor Process HMM
• Unsupervised Part of Speech Induction
• Phil Blunsom
• Unsupervised Translation Induction
• Chinese Abbreviations
• Monolingual Corpora
• A Framework for Unsupervised
• Natural Language
• Morphology Induction
• A Bayesian Approach
• Unsupervised Semantic
• Role Induction
• scientific reports
• model language
• process natural language