waashk/dblp huggingface dataset:
caramel: a flexible model for interaction between the cognitive processes underlying natural language understanding. in this paper we present a general natural language processing system called caramel (in french: compr&eacute;hension automatique de r&eacute;cits, apprentissage et mod&eacute;lisation des &eacute;changes langagiers). over the last few years our group has developed many programs to deal with different aspects of natural language processing. this paper describes a general architecture that integrates them in a flexible way, and provides a control strategy capable of adapting itself to the requirements of a particular task. the model is composed of three fundamental elements:- a structured memory containing permanent knowledge and working structures of the system- a set of processes, dedicated to the execution of the various cognitive tasks- a supervisor, whose function is to trigger, to run coherently and to synchronize the processes.the system contains a kind of blackboard, which is enhanced with a control mechanism driven by meta-rules. this architecture is fully implemented. we are currently developing the meta-rules necessary to use the model for various tasks.
problem localization strategies for pramatics processing in natural-language front ends. problem localization is the identification of the most significant failures in the and-or tree resulting from an unsuccessful attempt to achieve a goal, for instance, in planning, backward-chaining inference, or top-down parsing. we examine heuristics and strategies for problem localization in the context of using a planner to check for pragmatic failures in natural language input to computer systems, such as a cooperative natural language interface to unix&trade; our heuristics call for selecting the most hopeful branch at ors, but the most problematic one at ands. surprise scores and special-purpose rules are the main strategies suggested to determine this.
sesame a portable data base interface generator. sesame is being developed to provide an easy access to the content of relational data bases to users without a specific computer training. queries are typed in natural language either freely or with a guided mode. the system dynamically proposes through menus the different words and phrases that can make up a query. users are able to exploit the results of their queries with standard electronic office tools or specialized applications.the sesame system is a user interface generator. to develop a particular application, different knowledge bases have to be built: lexicon, conceptual schema of the data base... knowledge base editors and design methodologies provide help for the development of applications.sesame is a good example of techniques created in research laboratories and applied to the development of an industrial product.
quasi-indexical reference in propositional semantic networks. we discuss how a deductive question-answering system can represent the beliefs or other cognitive states of users, of other (interacting) systems, and of itself. in particular, we examine the representation of first-person beliefs of others (e.g., the <u>system's</u> representation of a <u>user's</u> belief that he himself is rich). such beliefs have as an essential component "quasi-indexical pronouns" (e.g., 'he himself'), and, hence, require for their analysis a method of representing these pronominal constructions and performing valid inferences with them. the theoretical justification for the approach to be discussed is the representation of <u>nested "de dicto"</u> beliefs (e.g., the system's belief that user-1 believes that system-2 believes that user-2 is rich). we discuss a computer implementation of these representations using the semantic network processing system (sneps) and an atn parser-generator with a question-answering capability.
the computation of word associations: comparing syntagmatic and paradigmatic approaches. it is shown that basic language processes such as the production of free word associations and the generation of synonyms can be simulated using statistical models that analyze the distribution of words in large text corpora. according to the law of association by contiguity, the acquisition of word associations can be explained by hebbian learning. the free word associations as produced by subjects on presentation of single stimulus words can thus be predicted by applying first-order statistics to the frequencies of word co-occurrences as observed in texts. the generation of synonyms can also be conducted on co-occurrence data but requires second-order statistics. the reason is that synonyms rarely occur together but appear in similar lexical neighborhoods. both approaches are systematically compared and are validated on empirical data. it turns out that for both tasks the performance of the statistical system is comparable to the performance of human subjects.
a constraint-based approach to translating anaphoric dependencies. the normal method for representing anaphoric dependencies in unification based grammar formalisms is that of re-entrance. in this paper, we address the problems that this representational device poses when such formalisms are used for translation. we demonstrate the inadequacies of existing proposals, and describe an approach which exploits the expressive possibilities of the equational constraint language in lfg and involves an inferential procedure combining underspecification in the statement of bilingual correspondences with the use of target language knowledge.
adjectival modification in text meaning representation. this work belongs to a family of research efforts, called microtheories and aimed at describing the static meaning of all lexical categories in several languages in the framework of the mikrokosmos project on computational semantics. the latter also involves other static microtheories describing world knowledge and syntax-semantics mapping as well as dynamic microtheories connected with the actual process of text analysis. this paper describes our approach to detecting and recording adjectival meaning, compares it with the body of knowledge on adjectives in literature and presents a detailed, practically tested methodology for the acquisition of lexical entries for adjectives. the work was based on the set of over 6,000 english and about 1,500 spanish adjectives obtained from task-oriented corpora.
pilot implementation of a bilingual knowledge bank. a bilingual knowledge bank is a syntactically and referentially structured pair of corpora, one being a translation of the other, in which translation units are cross-coded between the corpora. a pilot implementation is described for a corpus of some 20,000 words each in english, french and esperanto which has been cross-coded between english and esperanto and between esperanto and french. the aim is to develop a corpus-based general-purpose knowledge source for applications in machine translation and computer-aided translation.
a cooperative yes-no query system featuring discourse particles. cooperative dialog systems will offer extended answers to questions, that is, they will volunteer information not explicitly asked for. a complete response will be complex and the member sentences will evince an extensive parallel, the indirect answer substituting an alternative for a focus in the question. research on discourse particles has shown that they are necessary to ensure coherence between adjacent sentences evincing an extensive parallel, that is, that they reflect discourse relations as given in complex answers, so that such answers emerge as core contexts. thus the proper mode of representation for discourse particles in a system coincides with the framework of cooperative question-answering. the passat system centers on the rle of particles in characterizing and reflecting relations such as underlie complex response.
compiling language models from a linguistically motivated unification grammar. systems now exist which are able to compile unification grammars into language models that can be included in a speech recognizer, but it is so far unclear whether non-trivial linguistically principled grammars can be used for this purpose. we describe a series of experiments which investigate the question empirically, by incrementally constructing a grammar and discovering what problems emerge when successively larger versions are compiled into finite state graph representations and used as language models for a medium-vocabulary recognition task.
evaluating natural language systems: a sourcebook approach. this paper reports progress in development of evaluation methodologies for natural language systems. without a common classification of the problems in natural language understanding authors have no way to specify clearly what their systems do, potential users have no way to compare different systems and researchers have no way to judge the advantages or disadvantages of different approaches to developing systems.
parallel intersection and serial composition of finite state transducers. we describe a linguistically expressive and easy to implement parallel semantics for quasi-deterministic finite state transducers(fsts) used as acceptors. algorithms are given for determining acceptance of pairs of phoneme strings given a parallel suite of such transducers and for constructing the equivalent single transducer by parallel intersection. an algorithm for constructing the serial composition of a sequence of such transducers is also given. this algorithm can produce generally nondeterministic fsts and an algorithm is presented for eliminating the unacceptable nondeterminism. finally, the work is discussed in the context of other work on finite state transducers.
constructing verb semantic classes for french: methods and evaluation. in this paper, we study a reformulation, which is better adapted to nlp, of the alternation system developed for english by b. levin. we have studied a set of 1700 verbs from which we explain how verb semantic classes can be built in a systematic way. the quality of the results w.r.t. semantic classifications such as wordnet is then evaluated.
perception, concepts and language road and ipage. a two-level natural language generation system for situation and action descriptions (sads) of a simulated assembly robot is presented. in the first step, multimodal information is used to obtain a conceptual representation (cr) of an event. the second step is the parallel, incremental surface realization of utterances from the robot's perspective based on the cr. theoretical issues addressed are semantics of sads and distribution of lexical and syntactic processing, leading to a natural type of incrementality in nlg.
deafault logic, natural language and generalized quantifiers. the use of default logic to represent various linguistic constructions is explored in this paper. default logic is then integrated into a theory of natural language semantics, namely generalized quantifiers. finally, properties of interest to the ai community such as the characterization of truth persistence and some inferential patterns are emphasized.
a connectionist model of some aspects of anaphor resolution. this paper describes some recent developments in language processing involving computational models which more closely resemble the brain in both structure and function. these models employ a large number of interconnected parallel computational units which communicate via weighted levels of excitation and inhibition. a specific model is described which uses this approach to process some fragments of connected discourse.
interactive speech understanding. this paper introduces a robust interactive method for speech understanding. the generalized lr parsing is enhanced in this approach. parsing proceeds from left to right correcting minor errors. when a very noisy portion is detected, the parser skips that portion using a fake nonterminal symbol. the unidentified portion is resolved by re-utterance of that portion which is parsed very efficiently by using the parse record of the first utterance. the user does not have to speak the whole sentence again. this method is also capable of handling unknown words, which is important in practical systems. detected unknown words can be incrementally incorporated into the dictionary after the interaction with the user. a pilot system has shown great effectiveness of this approach.
bi-directional lr parsing from an anchor word for speech recognition. this paper introduces a new technique of parsing sentences from an arbitrary word which is highly reliable or semantically important. this technique adopts an efficient lr parsing method and uses a reverse lr table constructed besides a standard lr table. this technique is particularly suitable in parsing a lattice of words hypothesized by a speech recognition module. if we choose anchor symbols in such a way that they are almost always acoustically reliable, the bi-directional lr parsing performs better against misrecognized words than the regular left-to-right lr parser, while most of the lr efficiency is preserved. a pilot implementation shows a 43% reduction of the error rate against the left-to-right lr method in parsing the speech input.
parsing noisy sentences. this paper describes a method to parse and understand a "noisy" sentence that possibly includes errors caused by a speech recognition device. our parser is connected to a speech recognition device which takes a continuously spoken sentence in japanese and produces a sequence of phonemes. the output sequence of phonemes can quite possibly include errors: altered phonemes, extra phonemes and missing phonemes. the task is to parse the noisy phoneme sequence and understand the meaning of the original input sentence, given an augmented context-free grammar whose terminal symbols are phonemes. a very efficient parsing method is required, as the task's search space is much larger than that of parsing un-noisy sentences. we adopt the generalized lr parsing algorithm, and a certain scoring scheme to select the most likely sentence out of multiple sentence candidates. the use of a confusion matrix, which is created in advance by analyzing a large set of input/output pairs, is discussed to improve the scoring accuracy. the system has been integrated into cmu's knowledge-based machine translation system.
a fast algorithm for the generation of referring expressions. we simplify previous work in the development of algorithms for the generation of referring expressions while at the same time taking account of psycholinguistic findings and transcript data. the result is a straightforward algorithm that is computationally tractable, sensitive to the preferences of human users, and reasonably domain-independent. we provide a specification of the resources a host system must provide in order to make use of the algorithm, and describe an implementation used in the idas system.
a cd-rom retrieval system with multiple dialogue agents. in this paper, we proposed a new dialogue system with multiple dialogue agents. in our new system, three types of agents: a) domain agents, b) strategy agents, and c) context agents were realized. they give the following advantages to the user:&bull; the domain agents make the user aware of the boundary between the domains.&bull; the strategy agents make the user aware of the difference between the strategies.&bull; the context agents help the user to deal with multiple goals.we expect that the complex behaviors of the system will become more visible to the user in different situations. the experimental results show that the user can retrieve effectively and obtain the expected goals easily by using these multiple agents.
concept and structure of semantic markers for machine translation in mu-project. this paper discusses the semantic features of nouns classified into categories in japanese-to-english translation, and proposes a system for semantic markers. in our system syntactic analysis is carried out by checking the semantic compatibility between verbs and nouns. the semantic structure of a sentence can be extracted at the same time as its syntactic analysis.we also use semantic markers to select words in the transfer phase for translation into english.the system of the semantic markers for nouns consists of 13 conceptional faccts including one facct for "others" (discussed later), and is made up of 49 filial slots (semantic markers) as terminals. we have tested about 3,000 sample abstracts in science and technological fields. our research has revealed that our method is extremely effective in determining the meanings of wago verbs (basic japanese verbs) which have broader concepts like english verbs, "make", "get", "take", "put", etc.
dutch cross serial dependencies in hpsg. we present an analysis of dutch cross serial dependencies in head-driven phrase structure grammar ([p&s(1994)]). we start out from the assumption that causative and perceptual verbs, like auxiliaries, can lexically 'raise' the arguments of the non-finite verbs they govern to their own list of arguments through "argument composition" ([h&n(1989)]).
lexical parallelism in text structure determination and content analysis. in this paper the problem is discussed about the text structure determination and content analysis by lexical parallelism, or the repetition of lexical items. intersentential relations are determined through the identical, partly identical or lexico-semantic repetition in japanese scientific texts. lexical parallelism ratio and lexical parallelism indicator distance are obtained on computer and by hand. and the application of the characteristics to automatic content analysis is dicsussed.
left-corner parsing and psychological plausibility. it is well known that even extremely limited centerembedding causes people to have difficulty in comprehension, but that left- and right-branching constructions produce no such effect. if the difficulty in comprehension is taken to be a result of processing load, as is widely assumed, then measuring the processing load induced by a parsing strategy on these constructions may help determine its plausibility as a psychological model. on this basis, it has been argued [aj91, jl83] that by identifying processing load with space utilization, we can rule out both top-down and bottom-up parsing as viable candidates for the human sentence processing mechanism, and that left-corner parsing represents a plausible alternative.examining their arguments in detail, we find difficulties with each presentation. in this paper we revise the argument and validate its central claim. in so doing, we discover that the key distinction between the parsing methods is not the form of prediction (top-down vs. bottom-up vs. left-corner), but rather the ability to instantiate the operation of composition.
lexicon features for japanese syntactic analysis in mu-project-je. in this paper, we focus on the features of a lexicon for japanese syntactic analysis in japanese-to-english translation. japanese word order is almost unrestricted and <u>kakuio-shi</u> (postpositional case particle) is an important device which acts as the case label (case marker) in japanese sentences. therefore case grammar is the most effective grammar for japanese syntactic analysis.the case frame governed by <u>yougen</u> and having surface case <u>(kakuio-shi)</u>, deep case (case label) and semantic markers for nouns is analyzed here to illustrate how we apply case grammar to japanese syntactic analysis in our system.the parts of speech are classified into 56 sub-categories.we analyze semantic features for nouns and pronouns classified into sub-categories and we present a system for semantic markers. lexicon formats for syntactic and semantic features are composed of different features classified by part of speech.as this system uses lisp as the programming language, the lexicons are written as s-expression in lisp, punched onto tapes, and stored as files in the computer.
probabilistic tree-adjoining grammar as a framework for statistical natural language processing. in this paper, i argue for the use of a probabilistic form of tree-adjoining grammar (tag) in statistical natural language processing. i first discuss two previous statistical approaches --- one that concentrates on the probabilities of structural operations, and another that emphasizes co-occurrence relationships between words. i argue that a purely structural apprach, exemplified by probabilistic context-free grammar, lacks sufficient sensitivity to lexical context, and, conversely, that lexical co-occurence analyses require a richer notion of locality that is best provided by importing some notion of structure.i then propose probabilistic tag as a framework for statistical language modelling, arguing that it provides an advantageous combination of structure, locality, and lexical sensitivity. issues in the acquisition of probabilistic tag and parameter estimation are briefly considered.
on the use of term associations in automatic information retrieval. it has been recognized that single words extracted from natural language texts are not always useful for the representation of information content. associated or related terms. and comples content identifiers derived from thesauruses and knowledge bases, or constructed by automatic word grouping techniques, have therefore been proposed for text identification purposes.the area of associative content analysis and information retrievl is reviewed in this study. the available experimental evidence shows that none of the existing or proposed methodologies are guaranteed to improve retrieval performance in a replicable manner for document collections in different subject areas. the associative techniques are most valuable for restricted environments covering narrow subject areas, or in iterative search situations where user inputs are available to refine previously available query formulations and search output.
semantic relevance and aspect dependency in a given subject domain: contents-driven algorithmic processing of fuzzy wordmeanings to form dynamic stereotype representations. cognitive principles underlying the (re-) construction of word meaning and/or world knowledge structures are poorly understood yet. in a rather sharp departure from more orthodox lines of introspective acquisition of structural data on meaning and knowledge representation in cognitive science, an empirical approach is explored that analyses natural language data statistically, represents its numerical findings fuzzy-set theoretically, and interprets its intermediate constructs (stereotype meaning points) topologically as elements of semantic space. as connotative meaning representations, these elements allow an aspect-controlled, contents-driven algorithm to operate which reorganizes them dynamically in dispositional dependency structures (dds-trees) which constitute a procedurally defined meaning representation format.
inducing information extraction systems for new languages via cross-language projection. information extraction (ie) systems are costly to build because they require development texts, parsing tools, and specialized dictionaries for each application domain and each natural language that needs to be processed. we present a novel method for rapidly creating ie systems for new languages by exploiting existing ie systems via cross-language projection. given an ie system for a source language (e.g., english), we can transfer its annotations to corresponding texts in a target language (e.g., french) and learn information extraction rules for the new language automatically. in this paper, we explore several ways of realizing both the transfer and learning processes using off-the-shelf machine translation systems, induced word alignment, attribute projection, and transformation-based learning. we present a variety of experiments that show how an english ie system for a plane crash domain can be leveraged to automatically create a french ie system for the same domain.