Most existing Natural Language Database Interfaces (NLDB) were designed to be used with database systems that provide very limited facilities for manipulating time-dependent data, and they do not support adequately temporal linguistic mechanisms (verb tenses, temporal adverbials, temporal subordinate clauses, etc.). The database community is becoming increasingly interested in temporal database systems, which are intended to store and manipulate in a principled manner information not only about the present, but also about the past and future. When interfacing to temporal databases, supporting temporal linguistic mechanisms becomes crucial.

We present a framework for constructing Natural Language Interfaces for Temporal Databases (NLTDB), which draws on research in tense and aspect theories, temporal logics and temporal databases. The framework consists of a temporal intermediate representation language, called TOP, an HPSG grammar that maps a wide range of questions involving temporal mechanisms to appropriate TOP expressions, and a provably correct method for translating from TOP to TSQL2, TSQL2 being a recently proposed temporal extension of the SQL database language. This framework was employed to implement a prototype NLTDB.

This paper describes the work carried out at the Center for Sprogteknologi in Copenhagen to validate the LE evaluation methodology developed by the LRE project TEMAA. TEMAA has developed a framework for the evaluation of LE products, implemented in a Parameterisable Testbed (PTB). The framework allows for a modular, formal and exible description of user requirements and objects of evaluation, it accommodates test methods of various kind and provides a methodology for assessing test results in the light of the requirements expressed by different user types. While the fundamentals of the TEMAA framework are meant to apply to adequacy evaluation of LE products in general, a detailed methodology has been worked out for the evaluation of spelling and grammar checkers, and applied to the concrete evaluation of Danish and Italian spelling checkers. The main focus of this paper is on showing that the general methodology provides a valid model for designing and carrying out a concrete evaluation, as in the case study on Danish spelling checkers.

The statistical induction of stochastic context free grammars from bracketed corpora with the Inside Outside Algorithm is an appealing method for grammar learning, but the computational complexity of this algorithm has made it impossible to generate a large scale grammar. Researchers from natural language processing and speech recognition have suggested various methods to reduce the computational complexity and, at the same time, guide the learning algorithm towards a solution by, for example, placing constraints on the grammar. We suggest a method that strongly reduces that computational cost of the algorithm without placing constraints on the grammar. This method can in principle be combined with any of the constraints on grammars that have been suggested in earlier studies. We show that it is feasible to achieve results equivalent to earlier research, but with much lower computational effort. After creating a small grammar, the grammar is incrementally increased while rules that have become obsolete are removed at the same time. We explain the modifications to the algorithm, give results of experiments and compare these to results reported in other publications.

This paper describes tactical generation in Turkish, a free constituent order language, in which the order of the constituents may change according to the information structure of the sentences to be generated. In the absence of any information regarding the information structure of a sentence (i.e. topic, focus, background, etc.), the constituents of the sentence obey a default order, but the order is almost freely changeable, depending on the constraints of the text flow or discourse. We have used a recursively structured finite state machine (much like a Recursive Transition Network (RTN)) for handling the changes in constituent order, implemented as a right-linear grammar backbone. Our implementation environment is the GenKit system, developed at Carnegie Mellon University, Center for Machine Translation. Morphological realization has been implemented using an external morphological analysis/generation component which performs concrete morpheme selection and handles morphographemic processes.

This paper deals with the development of parsing techniques for the analysis of natural language sentences. We present a paradigm of a multi- path shift-reduce parser which combines two differently structured computational subsystems. The first uses information concerning native speakers' preferences, and the second deals with the linguistic knowledge. To apply preferences on parsing, we propose a method to rank the alternative partial analyses on the basis of parse context and frequency of use effects. The method is mainly based on psycholinguistic evidence, since we hope eventually to build a parser working as closely as possible to the way native speakers analyse natural sentences. We also discuss in detail techniques for optimizing the effectiveness of the proposed model. The system has worked successfully in parsing sentences in Modern Greek, a language where the relatively free word order characteristic results in many ambiguity problems. The proposed parsing model is consistent with many directions in the field of preference-based parsing, and it is proved to be adequate in building effective and maintainable natural language analysers. It is believed that this model can also be used in parsing sentences in languages other than Greek.

With the emergence of broad-coverage parsers, quantitative evaluation of parsers becomes increasingly more important. We propose a dependency-based method for evaluating broad-coverage parsers that offers more meaningful performance measures than previous approaches. We also present a structural pattern-matching mechanism that can be used to eliminate inconsequential differences among different parse trees. Previous evaluation methods have only evaluated the overall performance of parsers. The dependency-based method can also evaluate parsers with respect to different kinds of grammatical relationships or different types of lexical categories. An algorithm for transforming constituency trees into dependency trees is presented, which makes the evaluation method applicable to both constituency grammars and dependency grammars.

This paper describes two experiments: one exploring the amount of information relevant to sense disambiguation contained in the part-of-speech field of entries in a Machine Readable Dictionary (MRD); the other, more practical, experiment attempts sense disambiguation of all content words in a text assigning MRD homographs as sense tags using only part-of-speech information. We have implemented a simple sense tagger which successfully tags 94% of words using this method. A plan to extend this work and implement an improved sense tagger is included.

In this paper, we present results of a project that investigated the application of lexicon based text retrieval techniques to Alternative and Augmentative Communication (AAC). As a practical outcome of this research, a communication aid based on message retrieval by key words was designed, implemented and evaluated. The message retrieval module in the system uses a large semantic lexicon, derived from the WordNet database, for query expansion. Trials have been carried out with the device to evaluate whether the approach is suitable for AAC, and to determine the semantic relations that lead to efficient message retrieval. The first part of this paper describes the background of the project and highlights the retrieval requirements for a communication aid, which differ considerably from the requirements in standard text retrieval. We then present the overall design of the WordKeys communication aid and describe the tasks of its sub-modules. We summarise trials that have been carried out to determine the effect of semantic query expansion on the success of message retrieval. Evaluation results show that information about word frequency can solve problems that occurred in the semantic query expansion because of taxonomies that have too many intermediate steps between closely related words. Finally, a user evaluation with the improved system showed that full text retrieval is an effective approach to message access in a communication aid.

Augmentative and Alternative Communication (AAC) is the field of study concerned with providing devices and techniques to augment the communicative ability of a person whose disability makes it difficult to speak or otherwise communicate in an understandable fashion. For several years, we have been applying natural language processing techniques to the field of AAC to develop intelligent communication aids that attempt to provide linguistically correct output while increasing communication rate. Previous effort has resulted in a research prototype called Compansion that expands telegraphic input. In this paper we describe that research prototype and introduce the Intelligent Parser Generator (IPG). IPG is intended to be a practical embodiment of the research prototype aimed at a group of users who have cognitive impairments that affect their linguistic ability. We describe both the theoretical underpinnings of Compansion and the practical considerations in developing a usable system for this population of users.