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At least 163 records · Page 9Linked to original sources

A framework for lexical representation

In this paper we present a unification-based lexical platform designed for highly inflected languages (like Roman ones). A formalism is proposed for encoding a lemma-based lexical source, well suited for linguistic generalizations. From this source, we automatically generate an allomorph indexed dictionary, adequate for efficient processing. A set of software tools have been implemented around this formalism: access libraries, morphological processors, etc.

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Robust Processing of Natural Language

Previous approaches to robustness in natural language processing usually treat deviant input by relaxing grammatical constraints whenever a successful analysis cannot be provided by ``normal'' means. This schema implies, that error detection always comes prior to error handling, a behaviour which hardly can compete with its human model, where many erroneous situations are treated without even noticing them. The paper analyses the necessary preconditions for achieving a higher degree of robustness in natural language processing and suggests a quite different approach based on a procedure for structural disambiguation. It not only offers the possibility to cope with robustness issues in a more natural way but eventually might be suited to accommodate quite different aspects of robust behaviour within a single framework.

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GRAMPAL: A Morphological Processor for Spanish implemented in Prolog

A model for the full treatment of Spanish inflection for verbs, nouns and adjectives is presented. This model is based on feature unification and it relies upon a lexicon of allomorphs both for stems and morphemes. Word forms are built by the concatenation of allomorphs by means of special contextual features. We make use of standard Definite Clause Grammars (DCG) included in most Prolog implementations, instead of the typical finite-state approach. This allows us to take advantage of the declarativity and bidirectionality of Logic Programming for NLP. The most salient feature of this approach is simplicity: A really straightforward rule and lexical components. We have developed a very simple model for complex phenomena. Declarativity, bidirectionality, consistency and completeness of the model are discussed: all and only correct word forms are analysed or generated, even alternative ones and gaps in paradigms are preserved. A Prolog implementation has been developed for both analysis and generation of Spanish word forms. It consists of only six DCG rules, because our {\em lexicalist\/} approach --i.e. most information is in the dictionary. Although it is quite efficient, the current implementation could be improved for analysis by using the non logical features of Prolog, especially in word segmentation and dictionary access.

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An Efficient Algorithm for Surface Generation

A method is given that "inverts" a logic grammar and displays it from the point of view of the logical form, rather than from that of the word string. LR-compiling techniques are used to allow a recursive-descent generation algorithm to perform "functor merging" much in the same way as an LR parser performs prefix merging. This is an improvement on the semantic-head-driven generator that results in a much smaller search space. The amount of semantic lookahead can be varied, and appropriate tradeoff points between table size and resulting nondeterminism can be found automatically.

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Specifying Logic Programs in Controlled Natural Language

Writing specifications for computer programs is not easy since one has to take into account the disparate conceptual worlds of the application domain and of software development. To bridge this conceptual gap we propose controlled natural language as a declarative and application-specific specification language. Controlled natural language is a subset of natural language that can be accurately and efficiently processed by a computer, but is expressive enough to allow natural usage by non-specialists. Specifications in controlled natural language are automatically translated into Prolog clauses, hence become formal and executable. The translation uses a definite clause grammar (DCG) enhanced by feature structures. Inter-text references of the specification, e.g. anaphora, are resolved with the help of discourse representation theory (DRT). The generated Prolog clauses are added to a knowledge base. We have implemented a prototypical specification system that successfully processes the specification of a simple automated teller machine.

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A Compositional Treatment of Polysemous Arguments in Categorial Grammar

We discuss an extension of the standard logical rules (functional application and abstraction) in Categorial Grammar (CG), in order to deal with some specific cases of polysemy. We borrow from Generative Lexicon theory which proposes the mechanism of {\em coercion}, next to a rich nominal lexical semantic structure called {\em qualia structure}. In a previous paper we introduced coercion into the framework of {\em sign-based} Categorial Grammar and investigated its impact on traditional Fregean compositionality. In this paper we will elaborate on this idea, mostly working towards the introduction of a new semantic dimension. Where in current versions of sign-based Categorial Grammar only two representations are derived: a prosodic one (form) and a logical one (modelling), here we introduce also a more detaled representation of the lexical semantics. This extra knowledge will serve to account for linguistic phenomena like {\em metonymy\/}.

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Bi-Lexical Rules for Multi-Lexeme Translation in Lexicalist MT

The paper presents a prototype lexicalist Machine Translation system (based on the so-called `Shake-and-Bake' approach of Whitelock (1992) consisting of an analysis component, a dynamic bilingual lexicon, and a generation component, and shows how it is applied to a range of MT problems. Multi-Lexeme translations are handled through bi-lexical rules which map bilingual lexical signs into new bilingual lexical signs. It is argued that much translation can be handled by equating translationally equivalent lists of lexical signs, either directly in the bilingual lexicon, or by deriving them through bi-lexical rules. Lexical semantic information organized as Qualia structures (Pustejovsky 1991) is used as a mechanism for restricting the domain of the rules.

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Heuristics and Parse Ranking

There are currently two philosophies for building grammars and parsers -- Statistically induced grammars and Wide-coverage grammars. One way to combine the strengths of both approaches is to have a wide-coverage grammar with a heuristic component which is domain independent but whose contribution is tuned to particular domains. In this paper, we discuss a three-stage approach to disambiguation in the context of a lexicalized grammar, using a variety of domain independent heuristic techniques. We present a training algorithm which uses hand-bracketed treebank parses to set the weights of these heuristics. We compare the performance of our grammar against the performance of the IBM statistical grammar, using both untrained and trained weights for the heuristics.

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The Use of Knowledge Preconditions in Language Processing

If an agent does not possess the knowledge needed to perform an action, it may privately plan to obtain the required information on its own, or it may involve another agent in the planning process by engaging it in a dialogue. In this paper, we show how the requirements of knowledge preconditions can be used to account for information-seeking subdialogues in discourse. We first present an axiomatization of knowledge preconditions for the SharedPlan model of collaborative activity (Grosz & Kraus, 1993), and then provide an analysis of information-seeking subdialogues within a general framework for discourse processing. In this framework, SharedPlans and relationships among them are used to model the intentional component of Grosz and Sidner's (1986) theory of discourse structure.

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Countability and Number in Japanese-to-English Machine Translation

This paper presents a heuristic method that uses information in the Japanese text along with knowledge of English countability and number stored in transfer dictionaries to determine the countability and number of English noun phrases. Incorporating this method into the machine translation system ALT-J/E, helped to raise the percentage of noun phrases generated with correct use of articles and number from 65% to 73%.

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Using Information Content to Evaluate Semantic Similarity in a Taxonomy

This paper presents a new measure of semantic similarity in an IS-A taxonomy, based on the notion of information content. Experimental evaluation suggests that the measure performs encouragingly well (a correlation of r = 0.79 with a benchmark set of human similarity judgments, with an upper bound of r = 0.90 for human subjects performing the same task), and significantly better than the traditional edge counting approach (r = 0.66).

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The Unsupervised Acquisition of a Lexicon from Continuous Speech

We present an unsupervised learning algorithm that acquires a natural-language lexicon from raw speech. The algorithm is based on the optimal encoding of symbol sequences in an MDL framework, and uses a hierarchical representation of language that overcomes many of the problems that have stymied previous grammar-induction procedures. The forward mapping from symbol sequences to the speech stream is modeled using features based on articulatory gestures. We present results on the acquisition of lexicons and language models from raw speech, text, and phonetic transcripts, and demonstrate that our algorithm compares very favorably to other reported results with respect to segmentation performance and statistical efficiency.

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Generic rules and non-constituent coordination

We present a metagrammatical formalism, {\em generic rules}, to give a default interpretation to grammar rules. Our formalism introduces a process of {\em dynamic binding} interfacing the level of pure grammatical knowledge representation and the parsing level. We present an approach to non-constituent coordination within categorial grammars, and reformulate it as a generic rule. This reformulation is context-free parsable and reduces drastically the search space associated to the parsing task for such phenomena.

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Report of the Study Group on Assessment and Evaluation

This is an interim report discussing possible guidelines for the assessment and evaluation of projects developing speech and language systems. It was prepared at the request of the European Commission DG XIII by an ad hoc study group, and is now being made available in the form in which it was submitted to the Commission. However, the report is not an official European Commission document, and does not reflect European Commission policy, official or otherwise. After a discussion of terminology, the report focusses on combining user-centred and technology-centred assessment, and on how meaningful comparisons can be made of a variety of systems performing different tasks for different domains. The report outlines the kind of infra-structure that might be required to support comparative assessment and evaluation of heterogenous projects, and also the results of a questionnaire concerning different approaches to evaluation.

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Text Segmentation Based on Similarity between Words

This paper proposes a new indicator of text structure, called the lexical cohesion profile (LCP), which locates segment boundaries in a text. A text segment is a coherent scene; the words in a segment are linked together via lexical cohesion relations. LCP records mutual similarity of words in a sequence of text. The similarity of words, which represents their cohesiveness, is computed using a semantic network. Comparison with the text segments marked by a number of subjects shows that LCP closely correlates with the human judgments. LCP may provide valuable information for resolving anaphora and ellipsis.

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Noun Phrase Reference in Japanese-to-English Machine Translation

This paper shows the necessity of distinguishing different referential uses of noun phrases in machine translation. We argue that differentiating between the generic, referential and ascriptive uses of noun phrases is the minimum necessary to generate articles and number correctly when translating from Japanese to English. Heuristics for determining these differences are proposed for a Japanese-to-English machine translation system. Finally the results of using the proposed heuristics are shown to have raised the percentage of noun phrases generated with correct use of articles and number in the Japanese-to-English machine translation system ALT-J/E from 65% to 77%.

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Speech Recognition by Composition of Weighted Finite Automata

We present a general framework based on weighted finite automata and weighted finite-state transducers for describing and implementing speech recognizers. The framework allows us to represent uniformly the information sources and data structures used in recognition, including context-dependent units, pronunciation dictionaries, language models and lattices. Furthermore, general but efficient algorithms can used for combining information sources in actual recognizers and for optimizing their application. In particular, a single composition algorithm is used both to combine in advance information sources such as language models and dictionaries, and to combine acoustic observations and information sources dynamically during recognition.

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