Geert-Jan M. Kruijff

Multi-modal combinatory categorial grammar

The paper shows how Combinatory Categorial Grammar (CCG) can be adapted to take advantage of the extra resource-sensitivity provided by the Categorial Type Logic framework. The resulting reformulation, Multi-Modal CCG, supports lexically specified control over the applicability of combinatory rules, permitting a universal rule component and shedding the need for language-specific restrictions on rules. We discuss some of the linguistic motivation for these changes, define the Multi-Modal CCG system and demonstrate how it works on some basic examples. We furthermore outline some possible extensions and address computational aspects of Multi-Modal CCG.

Coupling CCG and Hybrid Logic Dependency Semantics

Categorial grammar has traditionally used the λ-calculus to represent meaning. We present an alternative, dependency-based perspective on linguistic meaning and situate it in the computational setting. This perspective is formalized in terms of hybrid logic and has a rich yet perspicuous propositional ontology that enables a wide variety of semantic phenomena to be represented in a single meaning formalism. Finally, we show how we can couple this formalization to Combinatory Categorial Grammar to produce interpretations compositionally.

Exploring syntactic relation patterns for question answering

In this paper, we explore the syntactic relation patterns for open-domain factoid question answering. We propose a pattern extraction method to extract the various relations between the proper answers and different types of question words, including target words, head words, subject words and verbs, from syntactic trees. We further propose a QA-specific tree kernel to partially match the syntactic relation patterns. It makes the more tolerant matching between two patterns and helps to solve the data sparseness problem. Lastly, we incorporate the patterns into a Maximum Entropy Model to rank the answer candidates. The experiment on TREC questions shows that the syntactic relation patterns help to improve the performance by 6.91 MRR based on the common features.

Talking robots with LEGO MindStorms

This paper shows how talking robots can be built from off-the-shelf components, based on the Lego MindStorms robotics platform. We present four robots that students created as final projects in a seminar we supervised. Because Lego robots are so affordable, we argue that it is now feasible for any dialogue researcher to tackle the interesting challenges at the robot-dialogue interface.

Information structure in topological dependency grammar

Topological Dependency Grammar (TDG) is a lexicalized dependency grammar formalism, able to model languages with a relatively free word order. In such languages, word order variation often has an important function: the realization of information structure. The paper discusses how to integrate information structure into TDG, and presents a constraint-based approach to modelling information structure and the various means to realize it, focusing on (possibly simultaneous use of) word order and tune.

Multilinguality in a text generation system for three Slavic languages

This paper describes a multilingual text generation system in the domain of CAD/CAM software instructions for Bulgarian, Czech and Russian. Starting from a language-independent semantic representation, the system drafts natural, continuous text as typically found in software manuals. The core modules for strategic and tactical generation are implemented using the KPML platform for linguistic resource development and generation. Prominent characteristics of the approach implemented are a treatment of multilinguality that makes maximal use of the commonalities between languages while also accounting for their differences and a common representational strategy for both text planning and sentence generation.

Discourse-level annotation for investigating information structure

We present discourse-level annotation of newspaper texts in German and English, as part of an ongoing project aimed at investigating information structure from a cross-linguistic perspective. Rather than annotating some specific notion of information structure, we propose a theory-neutral annotation of basic features at the levels of syntax, prosody and discourse, using treebank data as a starting point. Our discourse-level annotation scheme covers properties of discourse referents (e.g., semantic sort, delimitation, quantification, familiarity status) and anaphoric links (coreference and bridging). We illustrate what investigations this data serves and discuss some integration issues involved in combining different levels of stand-off annotations, created by using different tools.

Generalizing dimensionality in combinatory categorial grammar

We extend Combinatory Categorial Grammar (CCG) with a generalized notion of multidimensional sign, inspired by the types of representations found in constraint-based frameworks like HPSG or LFG. The generalized sign allows multiple levels to share information, but only in a resource-bounded way through a very restricted indexation mechanism. This improves representational perspicuity without increasing parsing complexity, in contrast to full-blown unification used in HPSG and LFG. Well-formedness of a linguistic expressions remains entirely determined by the CCG derivation. We show how the multidimensionality and perspicuity of the generalized signs lead to a simplification of previous CCG accounts of how word order and prosody can realize information structure.

Binding across Boundaries

The meaning of an utterance is normally contextual in that a speaker may present parts of it as relying on the preceding discourse context. Linguistically, there are various ways in which this reference to a larger context can manifest itself: For example, information structure, contextual reference, or entailments arising from aspectual structure. How (and whether) we can embed the meaning into the larger context then influences the coherence and actual interpretation of the uttered meaning.

Text Structuring in a Multilingual System for Generation of Instructions

The approach presented in this paper has been developed in the context of the international project called AGILE (Automatic Generation of Instructions in Languages of Eastern Europe)1. The overall aim of the project is to develop a multilingual system for generating continuous instructional texts in Bulgarian, Czech and Russian [2]. The project is concerned mainly with (i) the development and adaptation of linguistic resources for the chosen languages, and (ii) the investigation and specification of text structuring strategies employed in those languages for the given type of texts. In the current paper, we concentrate on the latter issues.