Research in the Language, Information and Computation Laboratory of the University of Pennsylvania

This report takes its name from the Computational Linguistics Feedback Forum (CLiFF), an informal discussion group for students and faculty. However the scope of the research covered in this report is broader than the title might suggest; this is the yearly report of the LINC Lab, the Language, Information and Computation Laboratory of the University of Pennsylvania. It may at first be hard to see the threads that bind together the work presented here, work by faculty, graduate students and postdocs in the Computer Science and Linguistics Departments, and the Institute for Research in Cognitive Science. It includes prototypical Natural Language fields such as: Combinatorial Categorial Grammars, Tree Adjoining Grammars, syntactic parsing and the syntax-semantics interface; but it extends to statistical methods, plan inference, instruction understanding, intonation, causal reasoning, free word order languages, geometric reasoning, medical informatics, connectionism, and language acquisition. Naturally, this introduction cannot spell out all the connections between these abstracts; we invite you to explore them on your own. In fact, with this issue it’s easier than ever to do so: this document is accessible on the “information superhighway”. Just call up http://www.cis.upenn.edu/~cliff-group/94/cliffnotes.html In addition, you can find many of the papers referenced in the CLiFF Notes on the net. Most can be obtained by following links from the authors’ abstracts in the web version of this report. The abstracts describe the researchers’ many areas of investigation, explain their shared concerns, and present some interesting work in Cognitive Science. We hope its new online format makes the CLiFF Notes a more useful and interesting guide to Computational Linguistics activity at Penn

DCU 250 Arabic dependency bank: an LFG gold standard resource for the Arabic Penn treebank

This paper describes the construction of a dependency bank gold standard for Arabic, DCU 250 Arabic Dependency Bank (DCU 250), based on the Arabic Penn Treebank Corpus (ATB) (Bies and Maamouri, 2003; Maamouri and Bies, 2004) within the theoretical framework of Lexical Functional Grammar (LFG). For parsing and automatically extracting grammatical and lexical resources from treebanks, it is necessary to evaluate against established gold standard resources. Gold standards for various languages have been developed, but to our knowledge, such a resource has not yet been constructed for Arabic. The construction of the DCU 250 marks the first step towards the creation of an automatic LFG f-structure annotation algorithm for the ATB, and for the extraction of Arabic grammatical and lexical resources

Automated Extraction of Tree Adjoining Grammars from a Treebank for Vietnamese

International audienceIn this paper, we present a system that automatically extracts lexicalized tree adjoining grammars (LTAG) from treebanks. We first discuss in detail extraction algorithms and compare them to previous works. We then report the first LTAG extraction result for Vietnamese, using a recently released Vietnamese treebank. The implementation of an open source and language independent system for automatic extraction of LTAG grammars is also discussed

Hindi Complex Predicates: Linguistic and Computational Approaches

Complex predicates that comprise of a noun and verb e.g. yaad kar 'memory do; remember' are a productive class of multi-words in Hindi. In this thesis, we examine the challenges of identification and representation for these complex predicates in Hindi. We design and implement their representation in a lexical semantic resource as well as in lexicalized computational grammars. As productive multi-word predicates, their accurate identification is a necessity for natural language processing applications. We use a combination of linguistic and computational approaches to address these challenges. We use these methods to demonstrate the semi-automatic creation of subcategorization frames for Hindi and the development of classes for nominal predicates. Finally, we demonstrate how linguistic features and computational tools can be used in tandem to automatically identify complex predicates from unseen text

Automated Extraction of Tree Adjoining Grammars from a Treebank for Vietnamese

International audienceIn this paper, we present a system that automatically extracts lexicalized tree adjoining grammars (LTAG) fromtreebanks.We first discuss in detail extraction algorithms and compare themto previous works. We then report the first LTAG extraction result for Vietnamese, using a recently released Vietnamese treebank. The implementation of an open source and language independent system for automatic extraction of LTAG grammars is also discussed

CLiFF Notes: Research In Natural Language Processing at the University of Pennsylvania

The Computational Linguistics Feedback Forum (CLIFF) is a group of students and faculty who gather once a week to discuss the members\u27 current research. As the word feedback suggests, the group\u27s purpose is the sharing of ideas. The group also promotes interdisciplinary contacts between researchers who share an interest in Cognitive Science. There is no single theme describing the research in Natural Language Processing at Penn. There is work done in CCG, Tree adjoining grammars, intonation, statistical methods, plan inference, instruction understanding, incremental interpretation, language acquisition, syntactic parsing, causal reasoning, free word order languages, ... and many other areas. With this in mind, rather than trying to summarize the varied work currently underway here at Penn, we suggest reading the following abstracts to see how the students and faculty themselves describe their work. Their abstracts illustrate the diversity of interests among the researchers, explain the areas of common interest, and describe some very interesting work in Cognitive Science. This report is a collection of abstracts from both faculty and graduate students in Computer Science, Psychology and Linguistics. We pride ourselves on the close working relations between these groups, as we believe that the communication among the different departments and the ongoing inter-departmental research not only improves the quality of our work, but makes much of that work possible