Articles

We present two approaches for syntactic and se- mantic transfer based on LFG f-structures and compare the results with existing co-description and restriction operator based approaches, fo- cusing on aspects of ambiguity preserving trans- fer, complex cases of syntactic structural mis- matches as well as on modularity and reusabil- ity. …...

Any large language processing software relies in its operation on heuristic decisions concerning the strategy of processing. These decisions are usually "hard-wired" into the software in the form of hand- crafted heuristic rules, independent of the nature of the processed texts. We propose an alternative, adaptive approach in which machine …...

This paper presents our work on accumulation of lexical sets which includes acquisition of dictionary resources and production of new lexical sets from this. The method for the acquisition, using a context-free syntax-directed translator and text modification techniques, proves easy-to-use, flexible, and efficient. Categories of production are analyzed, and basic …...

In this paper we specifically address questions of polysemy with respect to verbs, and how regular extensions of meaning can be achieved through the adjunction of particular syntactic phrases. We see verb classes as the key to making gen- eralizations about regular extensions of mean- ing. Current approaches to English …...

In this paper, we present a stochastic language mod- eling tool which aims at retrieving variable-length phrases (multigrams), assuming bigram dependen- cies between them. The phrase retrieval can be in- termixed with a phrase clustering procedure, so that the language data are iteratively structured at both a paradigmatic and a …...

Implemented methods for proper names recognition rely on large gazetteers of common proper nouns and a set of heuristic rules (e.g. Mr. as an indicator of a PERSON entity type). Though the performance of current PN recognizers is very high (over 90%), it is important to note that this problem …...

In this paper, we propose a generalization of Centenng Theory (CT) (Grosz, Joshi, Weinstein (1995)) called Veins Theory (VT), which extends the applicability of centering rules from local to global discourse. A key` facet of the theory involves the idenufication of <<veins>> over discourse structure trees such as those defined …...

The task of aligning sentences in parallel corpora of two languages has been well studied using pure sta- tistical or linguistic models. We developed a linguis- tic method based on lexical matching with a bilin- gual dictionary and two statistical methods based on sentence length ratios and sentence offset prob- …...

Bilingual news article alignment methods based on multi-lingual information retrieval have been shown to be successful for the automatic production of so-called noisy-parallel corpora. In this paper we compare the use of machine translation (MT) to the commonly used dictionary term lookup (DTL) method for Reuter news article alignment in …...

The previous English-Korean MT system that was the transfer-based MT system and applied to only written text enumerated a following brief list of the problems that had not seemed to be easy to solve in the near future : 1) processing of non-continuous idiomatic expressions 2) reduction of too many …...

In this study, a learning device based on the PAT- tree data structures was developed. The original PAT-trees were enhanced with the deletion function to emulate human learning competence. The learning process worked as follows. The linguistic patterns from the text corpus are inserted into the PAT-tree one by one. …...

Word sense disambiguation for unrestricted text is one of the most difficult tasks in the fields of computational linguistics. The crux of the problem is to discover a model that relates the intended sense of a word with its context. This paper describes a general framework for adaptive conceptual word …...

Recently, language barrier becomes the major problem for people to search, retrieve, and understand WWW documents in different languages. This paper deals with query translation issue in cross-language information retrieval, proper names in particular. Models for name identification, name translation and name searching are presented. The recall rates and the …...

Finding simple, non-recursive, base noun phrases is an important subtask for many natural language processing applications. While previous empirical methods for base NP identification have been rather complex, this paper instead proposes a very simple algorithm that is tailored to the relative simplicity of the task. In particular, we present …...

In this paper we view Lexicalized Tree Adjoining Grammars as the compilation of a more abstract and modular layer of linguistic description :the metagrammar (MG). MG provides a hierarchical representation of lexico- syntactic descriptions and principles that capture the well-formedness of lexicalized structures, expressed using syntactic functions. This makes it …...

This study exploits statistical redundancy inherent in natural language to automatically predict scores for essays. We use a hybrid feature identification method, including syntactic structure analysis, rhetorical structure analysis, and topical analysis, to score essay responses from test-takers of the Graduate Management Admissions Test (GMAT) and the Test of Written …...

This paper describes a new scoring algorithm that supports comparison of linguistically annotated data from noisy sources. The new algorithm generalizes the Message Understanding Conference (MUC) Named Entity scoring algorithm, using a compari- son based on explicit alignment of the underlying texts, followed by a scoring phase. The scoring procedure …...

This paper describes a domain independent, automat- ically trained call router which directs customer calls based on their response to an open-ended "How may I di- rect your call?" query. Routing behavior is trained from a corpus of transcribed and hand-routed calls and then carried out using vector-based information retrieval …...

One of the most exciting recent directions in machine learning is the discovery that the combination of multiple classifiers often results in significantly better performance than what can be achieved with a single classifier. In this paper, we first show that the errors made from three different state of the …...

It seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. Interestingly, state of the art language models for speech recognition are based on a very crude linguistic model, namely conditioning the probability of a word on a small fixed …...