Constraints and Type Hierarchies for Korean Serial Verb Constructions - An Analytic Study within the HPSG Framework -

PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 200

Modeling information structure in a cross-linguistic perspective

This study makes substantial contributions to both the theoretical and computational treatment of information structure, with a specific focus on creating natural language processing applications such as multilingual machine translation systems. The present study first provides cross-linguistic findings in regards to information structure meanings and markings. Building upon such findings, the current model represents information structure within the HPSG/MRS framework using Individual Constraints. The primary goal of the present study is to create a multilingual grammar model of information structure for the LinGO Grammar Matrix system. The present study explores the construction of a grammar library for creating customized grammar incorporating information structure and illustrates how the information structure-based model improves performance of transfer-based machine translation

The Relationship between Semantic Similarity and Subcategorization Frames in English: A Stochastic Test Using ICE-GB and WordNet

PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

FAQ : Do Non-linguists Share the Same Intuition as Linguists?

When studying the nature of human language, we frequently ask ourselves the following question: Do native speakers agree with our judgments of the sentences in question? Many of us have encountered quite a few sentences which linguists report to be grammatical but which non-linguists find ungrammatical. Linguists try their best in their language analyses to accommodate the native speakers intuitions in a systematic way, but these efforts are mostly confined to the so-called informal method. A natural question that arises is if the naïve native speakers would agree to the introspective acceptability judgments. In order to properly answer this question, a rigorous and formal method that will ensure more systematic and fine-grained results is required. This paper aims to address questions relating to this issue, exclusively focusing on Korean. The present work intends to provide some substantive discussion on how similar or different linguists intuitions are to/from those of the general public estimating grammatical acceptability. Our main experiment was carried out with 138 subjects, using about one thousand sentences excerpted from two volumes of a linguistic journal. We calculated the convergence rate focusing on the pairwise sentences in the data, and the rate was computed to be 84.75%. This measure is somewhat lower than the convergence rate of 95% reported in Sprouse et al. (2013) for the English data

Modeling information structure in a cross-linguistic perspective

This study makes substantial contributions to both the theoretical and computational treatment of information structure, with a specific focus on creating natural language processing applications such as multilingual machine translation systems. The present study first provides cross-linguistic findings in regards to information structure meanings and markings. Building upon such findings, the current model represents information structure within the HPSG/MRS framework using Individual Constraints. The primary goal of the present study is to create a multilingual grammar model of information structure for the LinGO Grammar Matrix system. The present study explores the construction of a grammar library for creating customized grammar incorporating information structure and illustrates how the information structure-based model improves performance of transfer-based machine translation

A Grammar Library for Information Structure

Thesis (Ph.D.)--University of Washington, 2014This dissertation makes substantial contributions to both the theoretical and computational treatment of information structure, with an eye toward creating natural language processing applications such as multilingual machine translation systems. The aim of the present dissertation is to create a grammar library of information structure for the LinGO Grammar Matrix system (Bender et al. 2010b). Information structure consists of focus, topic, contrast, and background, and refers to how speakers package semantic content they wish to convey to listeners. The information structure of individual sentences is crucial to understanding the cohesiveness of larger segments of text. Despite the crucial role information structure plays in conveying meaning, there is insufficient research on how computational language models might successfully incorporate information structure marking particularly from a multilingual perspective. Part I introduces the current study, and gives some background information. Part II provides cross-linguistic findings about information structure meanings and markings. Part III exploits a naturally occurring text in four languages (e.g. English, Spanish, Russian, and Korean) to formulate a cross-linguistic generalization about distributional properties of information structure. Drawing from these cross-linguistic findings, Part IV shows how information structure can be represented within the HPSG/MRS framework (Pollard and Sag, 1994; Copestake et al., 2005). Part V explores the construction of a grammar library for creating customized grammars incorporating information structure and shows how the information structure-based model improves performance of transfer-based machine translation