Searcharxiv⌕ Search

SEARCH · Searcharxiv

Results for “cmp-lg”

Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4Linked to original sources

Interlanguage Signs and Lexical Transfer Errors

A theory of interlanguage (IL) lexicons is outlined, with emphasis on IL lexical entries, based on the HPSG notion of lexical sign. This theory accounts for idiosyncratic or lexical transfer of syntactic subcategorisation and idioms from the first language to the IL. It also accounts for developmental stages in IL lexical grammar, and grammatical variation in the use of the same lexical item. The theory offers a tool for robust parsing of lexical transfer errors and diagnosis of such errors.

cmp-lg↗

Extraction in Dutch with Lexical Rules

Unbounded dependencies are often modelled by ``traces'' (and ``gap threading'') in unification-based grammars. Pollard and Sag, however, suggest an analysis of extraction based on lexical rules, which excludes the notion of traces (P&S 1994, Chapter 9). In parsing, it suggests a trade of indeterminism for lexical ambiguity. This paper provides a short introduction to this approach to extraction with lexical rules, and illustrates the linguistic power of the approach by applying it to particularly idiosyncratic Dutch extraction data.

cmp-lg↗

Free-ordered CUG on Chemical Abstract Machine

We propose a paradigm for concurrent natural language generation. In order to represent grammar rules distributively, we adopt categorial unification grammar (CUG) where each category owns its functional type. We augment typed lambda calculus with several new combinators, to make the order of lambda-conversions free for partial / local processing. The concurrent calculus is modeled with Chemical Abstract Machine. We show an example of a Japanese causative auxiliary verb that requires a drastic rearrangement of case domination.

cmp-lg↗

Abstract Generation based on Rhetorical Structure Extraction

We have developed an automatic abstract generation system for Japanese expository writings based on rhetorical structure extraction. The system first extracts the rhetorical structure, the compound of the rhetorical relations between sentences, and then cuts out less important parts in the extracted structure to generate an abstract of the desired length. Evaluation of the generated abstract showed that it contains at maximum 74\% of the most important sentences of the original text. The system is now utilized as a text browser for a prototypical interactive document retrieval system.

cmp-lg↗

The Speech-Language Interface in the Spoken Language Translator

The Spoken Language Translator is a prototype for practically useful systems capable of translating continuous spoken language within restricted domains. The prototype system translates air travel (ATIS) queries from spoken English to spoken Swedish and to French. It is constructed, with as few modifications as possible, from existing pieces of speech and language processing software. The speech recognizer and language understander are connected by a fairly conventional pipelined N-best interface. This paper focuses on the ways in which the language processor makes intelligent use of the sentence hypotheses delivered by the recognizer. These ways include (1) producing modified hypotheses to reflect the possible presence of repairs in the uttered word sequence; (2) fast parsing with a version of the grammar automatically specialized to the more frequent constructions in the training corpus; and (3) allowing syntactic and semantic factors to interact with acoustic ones in the choice of a meaning structure for translation, so that the acoustically preferred hypothesis is not always selected even if it is within linguistic coverage.

cmp-lg↗

An Efficient Probabilistic Context-Free Parsing Algorithm that Computes Prefix Probabilities

We describe an extension of Earley's parser for stochastic context-free grammars that computes the following quantities given a stochastic context-free grammar and an input string: a) probabilities of successive prefixes being generated by the grammar; b) probabilities of substrings being generated by the nonterminals, including the entire string being generated by the grammar; c) most likely (Viterbi) parse of the string; d) posterior expected number of applications of each grammar production, as required for reestimating rule probabilities. (a) and (b) are computed incrementally in a single left-to-right pass over the input. Our algorithm compares favorably to standard bottom-up parsing methods for SCFGs in that it works efficiently on sparse grammars by making use of Earley's top-down control structure. It can process any context-free rule format without conversion to some normal form, and combines computations for (a) through (d) in a single algorithm. Finally, the algorithm has simple extensions for processing partially bracketed inputs, and for finding partial parses and their likelihoods on ungrammatical inputs.

cmp-lg↗

Using default inheritance to describe LTAG

We present the results of an investigation into how the set of elementary trees of a Lexicalized Tree Adjoining Grammar can be represented in the lexical knowledge representation language DATR (Evans & Gazdar 1989a,b). The LTAG under consideration is based on the one described in Abeille et al. (1990). Our approach is similar to that of Vijay-Shanker & Schabes (1992) in that we formulate an inheritance hierarchy that efficiently encodes the elementary trees. However, rather than creating a new representation formalism for this task, we employ techniques of established utility in other lexically-oriented frameworks. In particular, we show how DATR's default mechanism can be used to eliminate the need for a non-immediate dominance relation in the descriptions of the surface LTAG entries. This allows us to embed the tree structures in the feature theory in a manner reminiscent of HPSG subcategorisation frames, and hence express lexical rules as relations over feature structures.

cmp-lg↗

NL Understanding with a Grammar of Constructions

We present an approach to natural language understanding based on a computable grammar of constructions. A "construction" consists of a set of features of form and a description of meaning in a context. A grammar is a set of constructions. This kind of grammar is the key element of Mincal, an implemented natural language, speech-enabled interface to an on-line calendar system. The system consists of a NL grammar, a parser, an on-line calendar, a domain knowledge base (about dates, times and meetings), an application knowledge base (about the calendar), a speech recognizer, a speech generator, and the interfaces between those modules. We claim that this architecture should work in general for spoken interfaces in small domains. In this paper we present two novel aspects of the architecture: (a) the use of constructions, integrating descriptions of form, meaning and context into one whole; and (b) the separation of domain knowledge from application knowledge. We describe the data structures for encoding constructions, the structure of the knowledge bases, and the interactions of the key modules of the system.

cmp-lg↗

An HPSG Parser Based on Description Logics

In this paper I present a parser based on Description Logics (DL) for a German HPSG -style fragment. The specified parser relies mainly on the inferential capabilities of the underlying DL system. Given a preferential default extension for DL disambiguation is achieved by choosing the parse containing a qualitatively minimal number of exceptions.

cmp-lg↗

Lexical Knowledge Representation in an Intelligent Dictionary Help System

The frame-based knowledge representation model adopted in IDHS (Intelligent Dictionary Help System) is described in this paper. It is used to represent the lexical knowledge acquired automatically from a conventional dictionary. Moreover, the enrichment processes that have been performed on the Dictionary Knowledge Base and the dynamic exploitation of this knowledge - both based on the exploitation of the properties of lexical semantic relations - are also described.

cmp-lg↗

Learning Unification-Based Natural Language Grammars

When parsing unrestricted language, wide-covering grammars often undergenerate. Undergeneration can be tackled either by sentence correction, or by grammar correction. This thesis concentrates upon automatic grammar correction (or machine learning of grammar) as a solution to the problem of undergeneration. Broadly speaking, grammar correction approaches can be classified as being either {\it data-driven}, or {\it model-based}. Data-driven learners use data-intensive methods to acquire grammar. They typically use grammar formalisms unsuited to the needs of practical text processing and cannot guarantee that the resulting grammar is adequate for subsequent semantic interpretation. That is, data-driven learners acquire grammars that generate strings that humans would judge to be grammatically ill-formed (they {\it overgenerate}) and fail to assign linguistically plausible parses. Model-based learners are knowledge-intensive and are reliant for success upon the completeness of a {\it model of grammaticality}. But in practice, the model will be incomplete. Given that in this thesis we deal with undergeneration by learning, we hypothesise that the combined use of data-driven and model-based learning would allow data-driven learning to compensate for model-based learning's incompleteness, whilst model-based learning would compensate for data-driven learning's unsoundness. We describe a system that we have used to test the hypothesis empirically. The system combines data-driven and model-based learning to acquire unification-based grammars that are more suitable for practical text parsing. Using the Spoken English Corpus as data, and by quantitatively measuring undergeneration, overgeneration and parse plausibility, we show that this hypothesis is correct.

cmp-lg↗

ProFIT: Prolog with Features, Inheritance and Templates

ProFIT is an extension of Standard Prolog with Features, Inheritance and Templates. ProFIT allows the programmer or grammar developer to declare an inheritance hierarchy, features and templates. Sorted feature terms can be used in ProFIT programs together with Prolog terms to provide a clearer description language for linguistic structures. ProFIT compiles all sorted feature terms into a Prolog term representation, so that the built-in Prolog term unification can be used for the unification of sorted feature structures, and no special unification algorithm is needed. ProFIT programs are compiled into Prolog programs, so that no meta-interpreter is needed for their execution. ProFIT thus provides a direct step from grammars developed with sorted feature terms to Prolog programs usable for practical NLP systems.

cmp-lg↗

Bottom-Up Earley Deduction

We propose a bottom-up variant of Earley deduction. Bottom-up deduction is preferable to top-down deduction because it allows incremental processing (even for head-driven grammars), it is data-driven, no subsumption check is needed, and preference values attached to lexical items can be used to guide best-first search. We discuss the scanning step for bottom-up Earley deduction and indexing schemes that help avoid useless deduction steps.

cmp-lg↗

Off-line Optimization for Earley-style HPSG Processing

A novel approach to HPSG based natural language processing is described that uses an off-line compiler to automatically prime a declarative grammar for generation or parsing, and inputs the primed grammar to an advanced Earley-style processor. This way we provide an elegant solution to the problems with empty heads and efficient bidirectional processing which is illustrated for the special case of HPSG generation. Extensive testing with a large HPSG grammar revealed some important constraints on the form of the grammar.

cmp-lg↗

Rapid Development of Morphological Descriptions for Full Language Processing Systems

I describe a compiler and development environment for feature-augmented two-level morphology rules integrated into a full NLP system. The compiler is optimized for a class of languages including many or most European ones, and for rapid development and debugging of descriptions of new languages. The key design decision is to compose morphophonological and morphosyntactic information, but not the lexicon, when compiling the description. This results in typical compilation times of about a minute, and has allowed a reasonably full, feature-based description of French inflectional morphology to be developed in about a month by a linguist new to the system.

cmp-lg↗

Utilization of a Lexicon for Spelling Correction in Modern Greek

In this paper we present an interactive spelling correction system for Modern Greek. The entire system is based on a morphological lexicon. Emphasis is given to the development of the lexicon, especially as far as storage economy, speed efficiency and dictionary coverage is concerned. Extensive research was conducted from both the computer engineering and linguisting fields, in order to describe inflectional morphology as economically as possible.

cmp-lg↗

A Robust and Efficient Three-Layered Dialogue Component for a Speech-to-Speech Translation System

We present the dialogue component of the speech-to-speech translation system VERBMOBIL. In contrast to conventional dialogue systems it mediates the dialogue while processing maximally 50% of the dialogue in depth. Special requirements like robustness and efficiency lead to a 3-layered hybrid architecture for the dialogue module, using statistics, an automaton and a planner. A dialogue memory is constructed incrementally.

cmp-lg↗

On Learning More Appropriate Selectional Restrictions

We present some variations affecting the association measure and thresholding on a technique for learning Selectional Restrictions from on-line corpora. It uses a wide-coverage noun taxonomy and a statistical measure to generalize the appropriate semantic classes. Evaluation measures for the Selectional Restrictions learning task are discussed. Finally, an experimental evaluation of these variations is reported.

cmp-lg↗