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arXiv1995

A Computational Treatment of HPSG Lexical Rules as Covariation in Lexical Entries

We describe a compiler which translates a set of HPSG lexical rules and their interaction into definite relations used to constrain lexical entries. The compiler ensures automatic transfer of properties unchanged by a lexical rule. Thus an operational semantics for the full lexical rule mechanism as used in HPSG linguistics is provided. Program transformation techniques are used to advance the resulting encoding. The final output constitutes a computational counterpart of the linguistic generalizations captured by lexical rules and allows ``on the fly'' application.

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arXiv1995

Constraint Logic Programming for Natural Language Processing

This paper proposes an evaluation of the adequacy of the constraint logic programming paradigm for natural language processing. Theoretical aspects of this question have been discussed in several works. We adopt here a pragmatic point of view and our argumentation relies on concrete solutions. Using actual contraints (in the CLP sense) is neither easy nor direct. However, CLP can improve parsing techniques in several aspects such as concision, control, efficiency or direct representation of linguistic formalism. This discussion is illustrated by several examples and the presentation of an HPSG parser.

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arXiv1995

SKOPE: A connectionist/symbolic architecture of spoken Korean processing

Spoken language processing requires speech and natural language integration. Moreover, spoken Korean calls for unique processing methodology due to its linguistic characteristics. This paper presents SKOPE, a connectionist/symbolic spoken Korean processing engine, which emphasizes that: 1) connectionist and symbolic techniques must be selectively applied according to their relative strength and weakness, and 2) the linguistic characteristics of Korean must be fully considered for phoneme recognition, speech and language integration, and morphological/syntactic processing. The design and implementation of SKOPE demonstrates how connectionist/symbolic hybrid architectures can be constructed for spoken agglutinative language processing. Also SKOPE presents many novel ideas for speech and language processing. The phoneme recognition, morphological analysis, and syntactic analysis experiments show that SKOPE is a viable approach for the spoken Korean processing.

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arXiv1995

Abstract Machine for Typed Feature Structures

This paper describes an abstract machine for linguistic formalisms that are based on typed feature structures, such as HPSG. The core design of the abstract machine is given in detail, including the compilation process from a high-level language to the abstract machine language and the implementation of the abstract instructions. The machine's engine supports the unification of typed, possibly cyclic, feature structures. A separate module deals with control structures and instructions to accommodate parsing for phrase structure grammars. We treat the linguistic formalism as a high-level declarative programming language, applying methods that were proved useful in computer science to the study of natural languages: a grammar specified using the formalism is endowed with an operational semantics.

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arXiv1995

NLG vs. Templates

One of the most important questions in applied NLG is what benefits (or `value-added', in business-speak) NLG technology offers over template-based approaches. Despite the importance of this question to the applied NLG community, however, it has not been discussed much in the research NLG community, which I think is a pity. In this paper, I try to summarize the issues involved and recap current thinking on this topic. My goal is not to answer this question (I don't think we know enough to be able to do so), but rather to increase the visibility of this issue in the research community, in the hope of getting some input and ideas on this very important question. I conclude with a list of specific research areas I would like to see more work in, because I think they would increase the `value-added' of NLG over templates.

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arXiv1995

LexGram - a practical categorial grammar formalism -

We present the LexGram system, an amalgam of (Lambek) categorial grammar and Head Driven Phrase Structure Grammar (HPSG), and show that the grammar formalism it implements is a well-structured and useful tool for actual grammar development.

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arXiv1995

Estimating Lexical Priors for Low-Frequency Syncretic Forms

Given a previously unseen form that is morphologically n-ways ambiguous, what is the best estimator for the lexical prior probabilities for the various functions of the form? We argue that the best estimator is provided by computing the relative frequencies of the various functions among the hapax legomena --- the forms that occur exactly once in a corpus. This result has important implications for the development of stochastic morphological taggers, especially when some initial hand-tagging of a corpus is required: For predicting lexical priors for very low-frequency morphologically ambiguous types (most of which would not occur in any given corpus) one should concentrate on tagging a good representative sample of the hapax legomena, rather than extensively tagging words of all frequency ranges.

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arXiv1995

A Formalism and an Algorithm for Computing Pragmatic Inferences and Detecting Infelicities

Since Austin introduced the term ``infelicity'', the linguistic literature has been flooded with its use, but no formal or computational explanation has been given for it. This thesis provides one for those infelicities that occur when a pragmatic inference is cancelled. Our contribution assumes the existence of a finer grained taxonomy with respect to pragmatic inferences. It is shown that if one wants to account for the natural language expressiveness, one should distinguish between pragmatic inferences that are felicitous to defeat and pragmatic inferences that are infelicitously defeasible. Thus, it is shown that one should consider at least three types of information: indefeasible, felicitously defeasible, and infelicitously defeasible. The cancellation of the last of these determines the pragmatic infelicities. A new formalism has been devised to accommodate the three levels of information, called ``stratified logic''. Within it, we are able to express formally notions such as ``utterance U presupposes P'' or ``utterance U is infelicitous''. Special attention is paid to the implications that our work has in solving some well-known existential philosophical puzzles. The formalism yields an algorithm for computing interpretations for utterances, for determining their associated presuppositions, and for signalling infelicitous utterances that has been implemented in Common Lisp. The algorithm applies equally to simple and complex utterances and sequences of utterances.

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arXiv1995

Phonological Derivation in Optimality Theory

Optimality Theory is a constraint-based theory of phonology which allows constraints to be violated. Consequently, implementing the theory presents problems for declarative constraint-based processing frameworks. On the basis of two regularity assumptions, that candidate sets are regular and that constraints can be modelled by transducers, this paper presents and proves correct algorithms for computing the action of constraints, and hence deriving surface forms.

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arXiv1995

TAKTAG: Two-phase learning method for hybrid statistical/rule-based part-of-speech disambiguation

Both statistical and rule-based approaches to part-of-speech (POS) disambiguation have their own advantages and limitations. Especially for Korean, the narrow windows provided by hidden markov model (HMM) cannot cover the necessary lexical and long-distance dependencies for POS disambiguation. On the other hand, the rule-based approaches are not accurate and flexible to new tag-sets and languages. In this regard, the statistical/rule-based hybrid method that can take advantages of both approaches is called for the robust and flexible POS disambiguation. We present one of such method, that is, a two-phase learning architecture for the hybrid statistical/rule-based POS disambiguation, especially for Korean. In this method, the statistical learning of morphological tagging is error-corrected by the rule-based learning of Brill [1992] style tagger. We also design the hierarchical and flexible Korean tag-set to cope with the multiple tagging applications, each of which requires different tag-set. Our experiments show that the two-phase learning method can overcome the undesirable features of solely HMM-based or solely rule-based tagging, especially for morphologically complex Korean.

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arXiv1995

A Morphographemic Model for Error Correction in Nonconcatenative Strings

This paper introduces a spelling correction system which integrates seamlessly with morphological analysis using a multi-tape formalism. Handling of various Semitic error problems is illustrated, with reference to Arabic and Syriac examples. The model handles errors vocalisation, diacritics, phonetic syncopation and morphographemic idiosyncrasies, in addition to Damerau errors. A complementary correction strategy for morphologically sound but morphosyntactically ill-formed words is outlined.

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arXiv1995

An Efficient Generation Algorithm for Lexicalist MT

The lexicalist approach to Machine Translation offers significant advantages in the development of linguistic descriptions. However, the Shake-and-Bake generation algorithm of (Whitelock, COLING-92) is NP-complete. We present a polynomial time algorithm for lexicalist MT generation provided that sufficient information can be transferred to ensure more determinism.

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arXiv1995

Memoization of Coroutined Constraints

Some linguistic constraints cannot be effectively resolved during parsing at the location in which they are most naturally introduced. This paper shows how constraints can be propagated in a memoizing parser (such as a chart parser) in much the same way that variable bindings are, providing a general treatment of constraint coroutining in memoization. Prolog code for a simple application of our technique to Bouma and van Noord's (1994) categorial grammar analysis of Dutch is provided.

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arXiv1995

Quantifiers, Anaphora, and Intensionality

The relationship between Lexical-Functional Grammar (LFG) {\em functional structures} (f-structures) for sentences and their semantic interpretations can be expressed directly in a fragment of linear logic in a way that correctly explains the constrained interactions between quantifier scope ambiguity, bound anaphora and intensionality. This deductive approach to semantic interpretaion obviates the need for additional mechanisms, such as Cooper storage, to represent the possible scopes of a quantified NP, and explains the interactions between quantified NPs, anaphora and intensional verbs such as `seek'. A single specification in linear logic of the argument requirements of intensional verbs is sufficient to derive the correct reading predictions for intensional-verb clauses both with nonquantified and with quantified direct objects. In particular, both de dicto and de re readings are derived for quantified objects. The effects of type-raising or quantifying-in rules in other frameworks here just follow as linear-logic theorems. While our approach resembles current categorial approaches in important ways, it differs from them in allowing the greater type flexibility of categorial semantics while maintaining a precise connection to syntax. As a result, we are able to provide derivations for certain readings of sentences with intensional verbs and complex direct objects that are not derivable in current purely categorial accounts of the syntax-semantics interface.

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arXiv1995

Statistical Decision-Tree Models for Parsing

Syntactic natural language parsers have shown themselves to be inadequate for processing highly-ambiguous large-vocabulary text, as is evidenced by their poor performance on domains like the Wall Street Journal, and by the movement away from parsing-based approaches to text-processing in general. In this paper, I describe SPATTER, a statistical parser based on decision-tree learning techniques which constructs a complete parse for every sentence and achieves accuracy rates far better than any published result. This work is based on the following premises: (1) grammars are too complex and detailed to develop manually for most interesting domains; (2) parsing models must rely heavily on lexical and contextual information to analyze sentences accurately; and (3) existing {$n$}-gram modeling techniques are inadequate for parsing models. In experiments comparing SPATTER with IBM's computer manuals parser, SPATTER significantly outperforms the grammar-based parser. Evaluating SPATTER against the Penn Treebank Wall Street Journal corpus using the PARSEVAL measures, SPATTER achieves 86\% precision, 86\% recall, and 1.3 crossing brackets per sentence for sentences of 40 words or less, and 91\% precision, 90\% recall, and 0.5 crossing brackets for sentences between 10 and 20 words in length.

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arXiv1995

Error-tolerant Finite State Recognition with Applications to Morphological Analysis and Spelling Correction

Error-tolerant recognition enables the recognition of strings that deviate mildly from any string in the regular set recognized by the underlying finite state recognizer. Such recognition has applications in error-tolerant morphological processing, spelling correction, and approximate string matching in information retrieval. After a description of the concepts and algorithms involved, we give examples from two applications: In the context of morphological analysis, error-tolerant recognition allows misspelled input word forms to be corrected, and morphologically analyzed concurrently. We present an application of this to error-tolerant analysis of agglutinative morphology of Turkish words. The algorithm can be applied to morphological analysis of any language whose morphology is fully captured by a single (and possibly very large) finite state transducer, regardless of the word formation processes and morphographemic phenomena involved. In the context of spelling correction, error-tolerant recognition can be used to enumerate correct candidate forms from a given misspelled string within a certain edit distance. Again, it can be applied to any language with a word list comprising all inflected forms, or whose morphology is fully described by a finite state transducer. We present experimental results for spelling correction for a number of languages. These results indicate that such recognition works very efficiently for candidate generation in spelling correction for many European languages such as English, Dutch, French, German, Italian (and others) with very large word lists of root and inflected forms (some containing well over 200,000 forms), generating all candidate solutions within 10 to 45 milliseconds (with edit distance 1) on a SparcStation 10/41. For spelling correction in Turkish, error-tolerant

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arXiv1995

The Replace Operator

This paper introduces to the calculus of regular expressions a replace operator, ->, and defines a set of replacement expressions that concisely encode several alternate variations of the operation. The basic case is unconditional obligatory replacement: UPPER -> LOWER Conditional versions of replacement, such as, UPPER -> LOWER || LEFT _ RIGHT constrain the operation by left and right contexts. UPPER, LOWER, LEFT, and RIGHT may be regular expressions of any complexity. Replace expressions denote regular relations. The replace operator is defined in terms of other regular expression operators using techniques introduced by Ronald M. Kaplan and Martin Kay in "Regular Models of Phonological Rule Systems" (Computational Linguistics 20:3 331-378. 1994).

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arXiv1996

Corpus Statistics Meet the Noun Compound: Some Empirical Results

A variety of statistical methods for noun compound analysis are implemented and compared. The results support two main conclusions. First, the use of conceptual association not only enables a broad coverage, but also improves the accuracy. Second, an analysis model based on dependency grammar is substantially more accurate than one based on deepest constituents, even though the latter is more prevalent in the literature.

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