waashk/dblp huggingface dataset:
devied and valency-oriented parsing in speech understanding. a parsing scheme for spoken utterances is proposed that deviates from traditional 'one go' left to right sentence parsing in that it devides the parsing process first into two separate parallel processes. verbal constituents and nominal phrases (including prepositonal phrases) are treated seperately and only brought together in an utterance parser. this allows especially the utterance parser to draw on valency information right from beginning when amalgamating the nominal constituents to the verbal core by means of binary sentence rules. the paper also discusses problems of representing the valency information in case-frames arising in a spoken language environment.
notions of correctness when evaluating protein name taggers. this paper introduces four different notions of correctness to be used when measuring the performance of protein name taggers, each of which reflects certain characteristics of the tagger under evaluation. the discussion regarding the different notions is centered around the evaluation of two protein name taggers; yapex, developed by the authors, and kex developed by fukuda et al. (1998). for the purpose of illustrating the difference between the ways of evaluation, both taggers are applied to a test corpus of 101 medline abstracts in which all occurrences of protein names have been marked up by domain experts.
improving smt quality with morpho-syntactic analysis. in the framework of statistical machine translation (smt), correspondences between the words in the source and the target language are learned from bilingual corpora on the basis of so-called alignment models. many of the statistical systems use little or no linguistic knowledge to structure the underlying models. in this paper we argue that training data is typically not large enough to sufficiently represent the range of different phenomena in natural languages and that smt can take advantage of the explicit introduction of some knowledge about the languages under consideration. the improvement of the translation results is demonstrated on two different german-english corpora.
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.
the procedure to construct a word predictor in a speech understanding system from a task-specific grammar defined in a cfg or a dcg. this paper describes a method for converting a task-dependent grammar into a word predictor of a speech understanding system. since the word prediction is a top-down operation, left recursive rules induces an infinite looping. we have solved this problem by applying an algorithm for bottom-up parsing.
termservice - an automated system for terminology services. the paper discusses the background, use environments and content of an automated system for multilingual terminology services, developed at the laboratory of mathematical linguistics of the institute of mathematics with computer centre affiliated to the bulgarian academy of sciences. particular emphasis is given to terminology acquistition and facilities for automated lexicography.
patrans- a patent translation system. this paper describes patrans-a fully automatic production mt system designed for producing raw translations of patent texts from english into danish. first we describe the backbone of the system: the eurotra research project and prototype. then we give an overview of the translation process and the basic functionality of patrans, and finally we describe some recent extensions for improving processing efficiency and the translation quality of unexpected input encountered in real-life texts.
lenient default unification for robust processing within unification based grammar formalisms. this paper describes new default unification, lenient default unification. it works efficiently, and gives more informative results because it maximizes the amount of information in the result, while other default unification maximizes it in the default. we also describe robust processing within the framework of hpsg. we extract grammar rules from the results of robust parsing using lenient default unification. the results of a series of experiments show that parsing with the extracted rules works robustly, and the coverage of a manually-developed hpsg grammar for penn treebank was greatly increased with a little overgeneration.
estimation of stochastic attribute-value grammars using an informative sample. we argue that some of the computational complexity associated with estimation of stochastic attribute value grammars can be reduced by training upon an informative subset of the full training set. results using the parsed wall street journal corpus show that in some circumstances, it is possible to obtain better estimation results using an informative sample than when training upon all the available material. further experimentation demonstrates that with unlexicalised models, a gaussian prior can reduce overfitting. however, when models are lexicalised and contain overlapping features, overfitting does not seem to be a problem, and a gaussian prior makes minimal difference to performance. our approach is applicable for situations when there are an infeasibly large number of parses in the training set, or else for when recovery of these parses from a packed representation is itself computationally expensive.
an indexing scheme for typed feature structures. this paper describes an indexing substrate for typed feature structures (istfs), which is an efficient retrieval engine for typed feature structures. given a set of typed feature structures, the istfs efficiently retrieves its subset whose elements are unifiable or in a subsumption relation with a query feature structure. the efficiency of the istfs is achieved by calculating a unifiability checking table prior to retrieval and finding the best index paths dynamically.
machine translation systems and computer dictionaries in the information service. ways of their development and operation. the paper outlines fields of application of machine translation systems and computer dictionaries in technical translation as well as possible ways of development and operation of computer dictionaries. interaction between linguists and commercial machine translation system is described.
interruptable transition networks. a specialized transition network mechanism, the interruptable transition network (itn) is used to perform the last of three stages in a multiprocessor syntactic parser. this approach can be seen as an exercise in implementing a parsing procedure of the active chart parser family.
evaluation metrics for knowledge-based machine translation. a methodology is presented for component-based machine translation (mt) evaluation through causal error analysis to complement existing global evaluation methods. this methodology is particularly appropriate for knowledge-based machine translation (kbmt) systems. after a discussion of mt evaluation criteria and the particular evaluation metrics proposed for kbmt, we apply this methodology to a large-scale application of the kant machine translation system, and present some sample results.
topic/focus articulation and intensional logic. a semantic analysis of topic and focus as two parts of tectogrammatical representation by means of transparent intensional logic (til) is presented. it is pointed out that two sentences (more precisely, their tectogrammatical representations) differing just in the topic/focus articulation (tfa) denote different propositions, i.e. that tfa has an effect upon the semantic content of the sentence. an informal short description of an algorithm handling the tfa in the translation of tectogrammatical representations into the constructions of til is added. the tfa algoriths divides a representation into two parts corresponding to the topic and focus; every part is analyzed (translated) in isolation and then the resulting construction is put together. the til construction discussed here reflect the scope of negation and some of the presuppositions observed.
a polynomial - order algorithm for optimal phrase sequence selection from a phrase lattice and its parallel layered implementation. this paper deals with a problem of selecting an optimal phrase sequence from a phrase lattice, which is often encountered in language processing such as word processing and post-processing for speech recognition. the problem is formulated as one of combinatorial optimization and a polynomial order algorithm is derived. this algorithm finds an optimal phrase sequence and its dependency structure simultaneously, and is therefore particularly suited for an interface between speech recognition and various language processing. what the algorithm does is numerical optimization rather than symbolic operation unlike conventional parsers. a parallel and layered structure to implement the algorithm is also presented. although the language taken up here is japanese, the algorithm can be extended to cover a wider family of languages.
measuring semantic coverage. the development of natural language processing systems is currently driven to a large extent by measures of knowledge-base size and coverage of individual phenomena relative to a corpus. while these measures have led to significant advances for knowledge-lean applications, they do not adequately motivate progress in computational semantics leading to the development of large-scale, general purpose nlp systems. in this article, we argue that depth of semantic representation is essential for covering a broad range of phenomena in the computational treatment of language and propose depth as an important additional dimension for measuring the semantic coverage of nlp systems. we propose an operationalization of this measure and show how to characterize an nlp system along the dimensions of size, corpus coverage, and depth. the proposed framework is illustrated using several prominent nlp systems. we hope the preliminary proposals made in this article will lead to prolonged debates in the field and will continue to be refined.
broad coverage automatic morphological segmentation of german words. a system for the automatic segmentation of german words into morphs was developed. the main linguistic knowledge sources used by the system are a word syntax and a morph dictionary. the syntax is written in the formalism of right linear regular grammars and comprises approximately 1, 400 rules describing the set of those sequences of morph classes which underlie syntactically well formed words. the morph dictionary contains almost 11, 000 morphs. each morph is assigned to up to 6 morph classes. - statistical evaluations with 6000 text words showed that more than 99% of the segmented words got a correct segmentation.
a framework for lexical selection in natural language generation. this paper describes a procedure for lexical selection of open-class lexical items in a natural language generation system. an optimum lexical selection module must be able to make realization decisions under varying contextual circumstances. first, it must be able to operate without the influence of context, based on meaning correspondences between elements of conceptual input and the lexical inventory of the target language. second, it must be able to use contextual constraints, as supported by collocational information in the generation lexicon. third, there must be an option of realizing input representations pronominally or through definite descriptions. finally, there must also be an option of using elliptical constactions. the nature of background knowledge and the algorithm we suggest for this task are described. the lexical selection procedure is a part of a comprehensive generation system, diogenes.
pos tagging using relaxation labelling. relaxation labelling is an optimization technique used in many fields to solve contraint satisfcation problems. the algorithm finds a combination of values for a set of variables such that satisfies -to the maximum possible degree- a set of given constraints. this paper describes some experiments performed applying it to pos tagging, and the results obtained. it also ponders the possibility of applying it to word sense disambiguation.
a metric for computational analysis of meaning: toward an applied theory of linguistic semantics. a metric for assessing the complexity of semantic (and pragmatic) analysis in natural language processing is proposed as part of a general applied theory of linguistic semantics for nlp. the theory is intended as a complete projection of linguistic semantics onto nlp and is designed as an exhaustive list of possible choices among strategies of semantic analysis at each level, from the word to the entire text. the alternatives are summarized in a chart, which can be completed for each existing or projected nlp system. the remaining components of the applied theory are also outlined.
referential properties of generic terms denoting things and situations. generic terms can be divided into two referentially different groups. generic term of the first group is a name (or a definite description) of the corresponding class of objects (of <u>jaguars in south america are extinct; the whale is a mammal</u>). as for generic terms of the second group, we propose to treat them as general terms (in the sense of w. o. quine): they are considered to be referentially incomplete expressions which, when constituting the theme of a generic proposition, undergo quantification which is expressed, explicitly or implicitly, inside the verb phrase.
on knowledge-based machine translation. this paper describes the design of the knowledge representation medium used for representing concepts and assertions, respectively, in a subworld chosen for a knowledge-based machine translation system. this design is used in the translator machine translation project. the knowledge representation language, or interlingua, has two components, dil and til. dil stands for 'dictionary of interlingua' and descibes the semantics of a subworld. til stands for 'text of interlingua' and is responsible for producing an interlingua text, which represents the meaning of an input text in the terms of the interlingua. we maintain that involved analysis of various types of linguistic and encyclopaedic meaning is necessary for the task of automatic translation. the mechanisms for extracting and manipulating and reproducing the meaning of texts will be reported in detail elsewhere. the linguistic (including the syntactic) knowledge about source and target languages is used by the mechanisms that translate texts into and from the interlingua. since interlingua is an artificial language, we can (and do, through til) control the syntax and semantics of the allowed interlingua elements. the interlingua suggested for translator has a broader coverage than other knowledge representation schemata for natural language. it involves the knowledge about discourse, speech acts, focus, time, space and other facets of the overall meaning of texts.
predicting co-occurrence restrictions by using semantic classifications in the lexicon. in this paper we investigate general principles of constructing semantic classifications that yield useful predictions concerning combinatory options of words. several semantic classes of russian words are discussed, implemented in an expert system named "lexicographer", the system being conceived as an aid both in the area of natural language processing and in traditional lexicography. semantic features proposed regulate co-occurence of verbs with their non-obligatory dependents - such as modifiers of place or time; instrumental and benefactive objects and the like.
hierarchical meaning representation and analysis of natural language documents. this paper attempts to systematize natural language analysis process by (1) use of a partitioned semantic network formalism as the meaning representation and (2) stepwise translation based on montague grammar. the meaning representation is obtained in two steps. the first step translates natural language into logical expression. the second step interprets logical expression to generate network structure. we have implemented set of programs which performs the stepwise translation. experiments are in progress for machine translation and question answering.
semantic dictionary viewed as a lexical database. in this paper an expert system is described which is called lexicographer and which aims at supplying the user with diverse information about russian words, including bibliographic information concerning individual lexical items. it is supposed that the system may be of use for a practical computational linguist and at the same time will serve as an instrument of linguistic research.
an english-japanese machine translation system based on formal semantics of natural language. this paper proposes a new model of machine translation. in this model, the lambda formula obtained from the syntactic and semantic analysis of a source language sentence is viewed as a target language generating function and the target language sentence is obtained as a result of evaluating the formula by functional application or &lambda;-calculus. this model provides a systematic and powerful way of incorporating human knowledge on the languages. a prototype is constructed on the lisp system. the performance was tested for four sample texts taken from existing technical reports and computer manuals.
combining functionality and object-orientedness for natural language processing. this paper proposes a method for organizing linguistic knowledge in both systematic and flexible fashion. we introduce a purely applicative language (pal) as an intermediate representation and an object-oriented computation mechanism for its interpretation. pal enables the establishment of a principled and well-constrained method of interaction among lexicon-oriented linguistic modules. the object-oriented computation mechanism provides a flexible means of abstracting modules and sharing common knowledge.
random generation of czech sentences. the experiments testing the theoretical adequacy and the practical usefulness of the functional generative description (fgd) are described. the fgd consists of a generative component, which, in the experimental version, has the shape of a context-free grammar combined with elements of dependency approach, and the other components having the form of pushdown store automata. the latter components have a transductive role, transducing the semantic (tectogrammatical) representations of sentences to the lower levels of the language system. the transduction is articulated into several steps corresponding more or less to the levels of language system (surface syntax, morphemics, morphophonemics, phonemics, or, as the case may be, graphemics) postulated in european structural linguistics. the theoretical and practical qualities of the system are evaluated.
surface and deep cases. in this paper we show the relation between the "surface (morphological) cases" and "deep cases" (participants), and the possible way to automate the creation of a syntactic dictionary provided with frames containing information about deep cases and their morphemic counterparts of particular lexical items (czech verbs).
maintaining consistency and plausibility in integrated natural language understanding. in this paper, we present an inference mechanism called the integrated parsing engine which provides a uniform abductive inference mechanism for natural language understanding. it can (1) make plausible assumptions, (2) reason with multiple alternatives, (3) switch the search process to the maximally plausible alternative, (4) detect contradiction and tame conclutions which depend on inconsistent assumptions, and (5) update plausibility factor of each belief based on new observations. we demonstrate that a natural language understanding system using the integrated parsing engine as a subsystem can pursue a guided search for most plausible interpretation by making use of syntax, semantics, and contextual information.
experiments with an mt-directed lexical knowledge bank. a crucial test for any mt system is its power to solve <u>lexical ambiguities</u>. the size of the lexicon, its structural principles and the availability of <u>extra-linguistic knowledge</u> are the most important aspects in this respect. this paper outlines the experimental development of the <u>swesil</u> system: a structured lexicon-based word expert system designed to play a pivotal role in the process of <u>distributed language translation</u> (dlt) which is being developed in the netherlands. it presents swesil's organizing principles, gives a short description of the present experimental set-up and shows how swesil is being tested at this moment.
japanese-english translation through internal expressions. this paper describes an approach to japanese-english translation through internal expressions which are similar to those used in our recent approach to english-japanese translation [2]. attention is focused on construction of the internal expressions of japanese sentences based on case structures of predicates and also conversion of the japanese internal expressions to the english ones for generating good english sentences in conventional use. finally, associated with translation, extraction of specified translated information from japanese patent claim sentences is described briefly.
empirical data and automatic analysis. the purpose of the present paper is to show the usefulness of (1) the computer processing of the manifold data of lexicographic works; and (2) the normal and reverse alphabetized concordances compiled on the basis of different texts.
english-japanese translation through case-structure conversion. this paper reports some trials on mechanical translation from english to japanese through a case structure constructed on hornby's verb patterns. though the general theoryof case structures is still at the beginning of study, it provides partial sentential patterns with rough but resonable classification labels. after determination of schematic dependency relations, multi-vocal problems for choosing appropriate equivalents are dissolved using subcategories of terms and cases. case structures of english are transformed into those of japanese if necessary, and from those, japanese sentences are generated by a japanese grammar.
building knowledge bases for the generation of software documentation. automated text generation requires a underlying knowledge base from which to generate, which is often difficult to produce. software documentation is one domain in which parts of this knowledge base may be derived automatically. in this paper, we describe drafter, an authoring support tool for generating usercentred software documentation, and in particular, we describe how parts of its required knowledge base can be obtained automatically.
feedback of correcting information in postediting to a machine translation system. this paper presents an attempt to construct a feedback system pecof which improves a japanese-english machine translation system by feedback of correcting information given by posteditors. pecof analyzes the error-correcting information by using an english-japanese machine translation system which works in the reverse direction to the original mt system, compares the intermediate expressions of the corrected patterns with those of the erroneous parts of the original mt output at every transfer stage and identifies the responsible parts of the original japanese-english mt system. then pecof corrects the irrelevant parts of the database or adds error correcting patterns to a document of postediting to ask users for further examinations for corrections.