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NPtool is a fast and accurate system for extracting noun phrases from English texts for the purposes of e.g. information retrieval, translation unit discovery, and corpus studies. After a general introduction, the system architecture is presented in outline. Then follows an examination of a recently written Constraint Syntax. An evaluation report concludes the paper.
Is it possible to specify a grammatical representation (descriptors and their application guidelines) to such a degree that it can be consistently applied by different grammarians e.g. for producing a benchmark corpus for parser evaluation? Arguments for and against have been given, but very little empirical evidence. In this article we report on a double-blind experiment with a surface-oriented morphosyntactic grammatical representation used in a large-scale English parser. We argue that a consistently applicable representation for morphology and also shallow syntax can be specified. A grammatical representation with a near-100% coverage of running text can be specified with a reasonable effort, especially if the representation is based on structural distinctions (i.e. it is structurally resolvable).
There are two main methodologies for constructing the knowledge base of a natural language analyser: the linguistic and the data-driven. Recent state-of-the-art part-of-speech taggers are based on the data-driven approach. Because of the known feasibility of the linguistic rule-based approach at related levels of description, the success of the data-driven approach in part-of-speech analysis may appear surprising. In this paper, a case is made for the syntactic nature of part-of-speech tagging. A new tagger of English that uses only linguistic distributional rules is outlined and empirically evaluated. Tested against a benchmark corpus of 38,000 words of previously unseen text, this syntax-based system reaches an accuracy of above 99%. Compared to the 95-97% accuracy of its best competitors, this result suggests the feasibility of the linguistic approach also in part-of-speech analysis.
The paper describes a substitutional approach to ellipsis resolution giving comparable results to Dalrymple, Shieber and Pereira (1991), but without the need for order-sensitive interleaving of quantifier scoping and ellipsis resolution. It is argued that the order-independence results from viewing semantic interpretation as building a description of a semantic composition, instead of the more common view of interpretation as actually performing the composition
We argue that the resource sharing that is commonly manifest in semantic accounts of coordination is instead appropriately handled in terms of structure-sharing in LFG f-structures. We provide an extension to the previous account of LFG semantics (Dalrymple et al., 1993b) according to which dependencies between f-structures are viewed as resources; as a result a one-to-one correspondence between uses of f-structures and meanings is maintained. The resulting system is sufficiently restricted in cases where other approaches overgenerate; the very property of resource-sensitivity for which resource sharing appears to be problematic actually provides explanatory advantages over systems that more freely replicate resources during derivation.
We show how categorial deduction can be implemented in higher-order (linear) logic programming, thereby realising parsing as deduction for the associative and non-associative Lambek calculi. This provides a method of solution to the parsing problem of Lambek categorial grammar applicable to a variety of its extensions.
We provide a constraint based computational model of linear precedence as employed in the HPSG grammar formalism. An extended feature logic which adds a wide range of constraints involving precedence is described. A sound, complete and terminating deterministic constraint solving procedure is given. Deterministic computational model is achieved by weakening the logic such that it is sufficient for linguistic applications involving word-order.
We describe a method for analysing the temporal structure of a discourse which takes into account the effects of tense, aspect, temporal adverbials and rhetorical structure and which minimises unnecessary ambiguity in the temporal structure. It is part of a discourse grammar implemented in Carpenter's ALE formalism. The method for building up the temporal structure of the discourse combines constraints and preferences: we use constraints to reduce the number of possible structures, exploiting the HPSG type hierarchy and unification for this purpose; and we apply preferences to choose between the remaining options using a temporal centering mechanism. We end by recommending that an underspecified representation of the structure using these techniques be used to avoid generating the temporal/rhetorical structure until higher-level information can be used to disambiguate.
This paper defines unification based ID/LP grammars based on typed feature structures as nonterminals and proposes a variant of Earley's algorithm to decide whether a given input sentence is a member of the language generated by a particular typed unification ID/LP grammar. A solution to the problem of the nonlocal flow of information in unification ID/LP grammars as discussed in Seiffert (1991) is incorporated into the algorithm. At the same time, it tries to connect this technical work with linguistics by presenting an example of the problem resulting from HPSG approaches to linguistics (Hinrichs and Nakasawa 1994, Richter and Sailer 1995) and with computational linguistics by drawing connections from this approach to systems implementing HPSG, especially the TROLL system, Gerdemann et al. (forthcoming).
In this paper we provide a probabilistic interpretation for typed feature structures very similar to those used by Pollard and Sag. We begin with a version of the interpretation which lacks a treatment of re-entrant feature structures, then provide an extended interpretation which allows them. We sketch algorithms allowing the numerical parameters of our probabilistic interpretations of HPSG to be estimated from corpora.
This paper presents an analysis of temporal anaphora in sentences which contain quantification over events, within the framework of Discourse Representation Theory. The analysis in (Partee 1984) of quantified sentences, introduced by a temporal connective, gives the wrong truth-conditions when the temporal connective in the subordinate clause is "before" or "after". This problem has been previously analyzed in (de Swart 1991) as an instance of the proportion problem, and given a solution from a Generalized Quantifier approach. By using a careful distinction between the different notions of reference time, based on (Kamp and Reyle 1993), we propose a solution to this problem, within the framework of DRT. We show some applications of this solution to additional temporal anaphora phenomena in quantified sentences.
In this paper, we propose a robust parser which can parse extragrammatical sentences. This parser can recover them using only syntactic information. It can be easily modified and extended because it utilize only syntactic information.
This paper investigates the syntax of extraposition in the HPSG framework. We present English and German data (partly taken from corpora), and provide an analysis using lexical rules and a nonlocal dependency. The condition for binding this dependency is formulated relative to the antecedent of the extraposed phrase, which entails that no fixed site for extraposition exists. Our analysis accounts for the interaction of extraposition with fronting and coordination, and predicts constraints on multiple extraposition.
This paper describes a method to automatically acquire the syntactic and semantic classifications of unknown words. Our method reduces the search space of the lexical acquisition problem by utilizing both the left and the right context of the unknown word. Link Grammar provides a convenient framework in which to implement our method.
This paper proposes a corpus-based language model for topic identification. We analyze the association of noun-noun and noun-verb pairs in LOB Corpus. The word association norms are based on three factors: 1) word importance, 2) pair co-occurrence, and 3) distance. They are trained on the paragraph and sentence levels for noun-noun and noun-verb pairs, respectively. Under the topic coherence postulation, the nouns that have the strongest connectivities with the other nouns and verbs in the discourse form the preferred topic set. The collocational semantics then is used to identify the topics from paragraphs and to discuss the topic shift phenomenon among paragraphs.
A bi-directional Korean/English dialog translation system is designed and implemented using the memory-based translation technique. The system KEMDT (Korean/English Memory-based Dialog Translation system) can perform Korean to English, and English to Korean translation using unified memory network and extended marker passing algorithm. We resolve the word order variation and frequent word omission problems in Korean by classifying the concept sequence element in four different types and extending the marker- passing-based-translation algorithm. Unlike the previous memory-based translation systems, the KEMDT system develops the bilingual memory network and the unified bi-directional marker passing translation algorithm. For efficient language specific processing, we separate the morphological processors from the memory-based translator. The KEMDT technology provides a hierarchical memory network and an efficient marker-based control for the recent example-based MT paradigm.
This paper is concerned with the detection and correction of sub-sentential English text errors. Previous spelling programs, unless restricted to a very small set of words, have operated as post-processors. And to date, grammar checkers and other programs which deal with ill-formed input usually step directly from spelling considerations to a full-scale parse, assuming a complete sentence. Work described below is aimed at evaluating the effectiveness of shallow (sub-sentential) processing and the feasibility of cooperative error checking, through building and testing appropriately an error-processing system. A system under construction is outlined which incorporates morphological checks (using new two-level error rules) over a directed letter graph, tag positional trigrams and partial parsing. Intended testing is discussed.
The work reported here is the result of a study done within a larger project on the ``Semantics of Natural Languages'' viewed from the field of Artificial Intelligence and Computational Linguistics. In this project, we have chosen a corpus of insurance claim reports. These texts deal with a relatively circumscribed domain, that of road traffic, thereby limiting the extra-linguistic knowledge necessary to understand them. Moreover, these texts present a number of very specific characteristics, insofar as they are written in a quasi-institutional setting which imposes many constraints on their production. We first determine what these constraints are in order to then show how they provide the writer with the means to create as succint a text as possible, and in a symmetric way, how they provide the reader with the means to interpret the text and to distinguish between its factual and argumentative aspects.