Ashwini Vaidya

Towards Identifying Hindi/Urdu Noun Templates in Support of a Large-Scale LFG Grammar

Complex predicates (CPs) are a highly productive predicational phenomenon in Hindi and Urdu and present a challenge for deep syntactic parsing. For CPs, a combination of a noun and light verb express a single event. The combinatorial preferences of nouns with one (or more) light verb is useful for predicting an instance of a CP. In this paper, we present a semi-automatic method to obtain noun groups based on their co-occurrences with light verbs. These noun groups represent the likelihood of a particular noun-verb combination in a large corpus. Finally, in order to encode this in an LFG grammar, we propose linking nouns with templates that describe preferable combinations with light verbs.

The Hindi/Urdu Treebank Project

The goal of Hindi/Urdu treebanking project is to build multi-layered treebanks that will provide both syntactic and semantic annotations. In the past two decades, dozens of treebanks have been created for languages such as Arabic, Chinese, Czech, English, French, German, and many more. Our treebanks differ from the previous treebanks in two important aspects: they are multi-representational, i.e., they include several layers of representation from the initial design; and they cover two standardized registers that are often considered separate languages: Hindi and Urdu.

Light verb constructions with `do' and `be' in Hindi: A TAG analysis

In this paper we present a Lexicalized Feature-based Tree-Adjoining Grammar analysis for a type of nominal predicate that occurs in combination with the light verbs “do” and “be” (Hindi kar and ho respectively). Light verb constructions are a challenge for computational grammars because they are a highly productive predicational strategy in Hindi. Such nominals have been discussed in the literature (Mohanan, 1997; Ahmed and Butt, 2011; Bhatt et al., 2013), but this work is a first attempt at a Tree-Adjoining Grammar (TAG) representation. We look at three possibilities for the design of elementary trees in TAG and explore one option in depth using Hindi data. In this analysis, the nominal is represented with all the arguments of the light verb construction, while the light verb adjoins into its elementary tree.

Adapting Predicate Frames for Urdu PropBanking

Hindi and Urdu are two standardized registers of what has been called the Hindustani language, which belongs to the IndoAryan language family. Although, both the varieties share a common grammar, they differ significantly in their vocabulary to an extent where both become mutually incomprehensible (Masica, 1993). Hindi draws its vocabulary from Sanskrit while Urdu draws its vocabulary from Persian, Arabic and even Turkish. In this paper, we present our efforts to adopt frames of nominal and verbal predicates that Urdu shares with either Hindi or Arabic for Urdu PropBanking. We discuss the feasibility of porting such frames from either of the sources (Arabic or Hindi) and also present a simple and reasonably accurate method to automatically identify the origin of Urdu words which is a necessary step in the process of porting such frames.