waashk/dblp huggingface dataset:
partial synthesis of sentences by coroutining constraints on different levels of well-formedness. we show how the two main characteristics of the illico natural language interface --- guided composition mode by partial synthesis, and the modularity of the encoding of linguistic knowledge specifying the lexical, syntactic, semantic and conceptual levels of well-formedness --- have lead us to develop an approach and a system in which all the constraints on the different levels of well-formedness are coroutined when the system analyzes a given sentence or synthesizes a partial one. we describe the principle of the general coroutining process and the associated prolog program.
mt and topic-based techniques to enhance speech recognition systems for professional translators. our principle objective was to reduce the error rate of speech recognition systems used by professional translators. our work concentrated on spanish-to-english translation. in a baseline study we estimated the error rate of an off-the-shelf recognizer to be 9.98%. in this paper we describe two independent methods of improving speech recognizers: a machine translation (mt) method and a topic-based one. an evaluation of the mt method suggests that the vocabulary used for recognition cannot be completely restricted to the set of translations produced by the mt system and a more sophisticated constraint system must be used. an evaluation of the topic-based method showed significant error rate reduction, to 5.07%.
categorial grammar and discourse representation theory. in this paper it is shown how simple texts that can be parsed in a lambek categorial grammar can also automatically be provided with a semantics in the form of a discourse representation structure in the sense of kamp [1981]. the assignment of meanings to texts uses the curry-howard-van benthem correspondence.
an ibm-pc environment for chinese corpus analysis. this paper describes a set of computer programs for chinese corpus analysis. these programs include (1) extraction of different characters, bigrams and words; (2) word segmentation based on bigram, maximal-matching and the combined technique; (3) identification of special terms; (4) chinese concordancing; (5) compiling collocation statistics and (6) evaluation utilities. these programs run on the ibm-pc and batch programs co-ordinate the use of these programs.
a project report on np: an assumption-based nl plan inference system that uses feature structures. this paper presents a project report on np, a working natural language plan inference system that uses feature structures and is based on assumptions. input to the system is in the form of feature structures, which can be taken directly from the output of a semantic parser. plan actions are represented by feature-structure plan schemata with preconditions, hierarchical decompositions, and effects. output is in the form of a network of believed assertions represented in a knowledge base, and can be reported, used to answer generation-system queries, or drive side-effecting demons. the plan inference component is implemented using a feature-structure-based inference engine and models of plan recognition, prediction, and inference. the inference engine is implemented using a rewriting system for pattern-matching, and an assumption-based truth maintenance system (atms) for conjunctions. the atms allows pre-instantiation of hypothetically known assertions and implications, which can significantly reduce processing time. the atms also permits simultaneous consideration of multiple possible inputs or multiple possible inferred plan outputs; these can be mutually conflicting or supportive. this capability will be important for disambiguation. the np system is used to infer dialog- and domain-level plans, among other types.original contributions include: a plan inference system that works directly from feature structures; a plan inference system that uses an atms and plan schema actions with preconditions and effects to infer hierarchical and chained plans; and, an inference engine that works with multiple feature-structure assertions and rules.
chinese string searching using the kmp algorithm. this paper is about the modification of kmp (knuth, morris and pratt) algorithm for string searching of chinese text. the difficulty is searching through a text string of single-and multi-byte characters. we showed that proper decoding of the input as sequences of characters instead of bytes is necessary. the standard kmp algorithm can easily be modified for chinese string searching but at the worst-case time-complexity of o(3n) in terms of the number of comparisons. the finite-automaton implementation can achieve worst-case time complexity of o(2n) but constructing the transition table depends on the size of the alphabet, &sigma;, which is large for chinese (for big-5, &sigma; > 13,000). a mapping technique reduces the size the alphabet to at most /p/ where p is the pattern string.
a pdp architecture for processing sentences with relative clauses. a modular parallel distributed processing architecture for parsing, representing and paraphrasing sentences with multiple hierarchical relative clauses is presented. a lowel-level network reads the segments of the sentence word by word into partially specified case-role representations of the acts. a higher-level network combines these representations into a list of complete act representations. this internal representation stores the information conveyed by the sentence independent of its linguistic form. the information can be output in natural language in different form or style, e.g. as a sequence of simple sentences or as a complex sentence consisting of relative clauses. generating output is independent from parsing, and what actually gets generated depends on the training of the generator modules.
learning part-of-speech guessing rules from lexicon: extension to non-concatenative operations. one of the problems in part-of-speech tagging of real-word texts is that of unknown to the lexicon words. in (mikheev, 1996), a technique for fully unsupervised statistical acquisition of rules which guess possible parts-of-speech for unknown words was proposed. one of the over-simplification assumed by this learning technique was the acquisition of morphological rules which obey only simple concatenative regularities of the main word with an affix. in this paper we extend this technique to the non-concatenative cases of suffixation and assess the gain in the performance.
hybrid neuro and rule-based part of speech taggers. a hybrid system for tagging part of speech is described that consists of a neuro tagger and a rule-based corrector. the neuro tagger is an initial-state annotator that uses different lengths of context based on longest context priority. its inputs are weighted by information gains that are obtained by information maximization. the rule-based corrector is constructed by a set of transformation rules to make up for the shortcomings of the neuro tagger. computer experiments show that almost 20% of the errors made by the neuro tagger are corrected by these transformation rules, so that the hybrid system can reach an accuracy of 95.5% counting only the ambiguous words and 99.1% counting all words when a small thai corpus with 22,311 ambiguous words is used for training. this accuracy is far higher than that using an hmm and is also higher than that using a rule-based model.
self-organizing chinese and japanese semantic maps. this paper describes a corpus-based connectionist approach to the development of self-organizing chinese and japanese semantic maps, proposing an improved coding method using tfidf term-weighting and newly introducing a numerical evaluation for objectively judging the results. the adaption of tfidf term-weighting is proved to be effective by experimental comparisons with five other coding methods. the effectiveness and necessity of the proposed method for creating semantic maps are clarified by comparisons with a conventional clustering technique and multivariate statistical analysis.
modularity, parallelism, and licensing in a principle-based parser for german. this paper presents a direct implementation of government-binding theory in a parser for german, which faithfully models the modular structure of the theory. the modular design yields a flexible environment, in which it is possible to define and test various versions of principles and parameters. the several modules of linguistic theory and the parser proper are interleaved in parallel fashion for early elimination of ungrammatical structures. efficient processing of global constraints is made possible by the concept of licensing, and the use of tree indexing techniques.
the influence of tagging on the classification of lexical complements. a large corpus (about 100 mb of text) was selected and examples of 750 frequently occurring verbs were tagged with their complement class as defined by a large computational syntactic dictionary, comlex syntax. this tagging task led to the refinement of already existing classes and to the addition of classes that had previously not been defined. this has resulted in the enrichment and improvement of the original comlex syntax dictionary. tagging also provides statistical data which will allow users to select more common complements of a particular verb and ignore rare usage. we discuss below some of the problems encountered in tagging and their resolution.
parsing against lexical ambiguity. marcus' original deterministic parsing included almost no part-of-speech ambiguity. in this paper, the addition of part-of-speech ambiguity to a deterministic parser written in prolog is described. to handle this ambiguity, it was necessary to add no special mechanisms to the parser. instead the grammar rules were made to enforce agreement, and reject ungrammatical sentences. the resulting system is very effective and covers many examples of ambiguity.
the transfer of finite verb forms in a machine translation system. this paper is based on work done jointly by hanne ruus, ebbe spang-hanssen and the author, all of the university of copenhagen. the work was done within the framework of eurotra and sponsored by the commission of the european community. work on this paper was begun whilst the author was at issco, geneva.
coordination in an axiomatic grammar. for some time there has been interest in the idea of parsing as deduction. here we present a grammatical formalism, 'axiomatic grammar', which is based upon a small number of linguistically motivated axioms and deduction rules. each axion or rule combines a 'category' with a string of words to form a further category. this contrasts with the usual 'tree-structure' approach to syntactic analysis where constituents are combined with each other to form a further constituent.we describe a grammar for english which has a good coverage of 'non-constituent' coordination. the grammar has been integrated with a toy semantics, and has been implemented in a left-to-right parser with incremental semantic interpretation. the parser does not suffer from spurious ambiguity.
dynamics, dependency grammar and incremental interpretation. the paper describes two equivalent grammatical formalisms. the first is a lexicalised version of dependeney grammar, and this can be used to provide tree-structured analyses of sentences (though some-what flatter than those usually provided by phrase structure grammars). the second is a new formalism, 'dynamic dependency grammar', which uses axioms and deduction rules to provide analyses of sentences in terms of transitions between states.a reformulation of dependency grammar using state transitions is of interest on several grounds. firstly, it can be used to show that incremental interpretation is possible without requiring notions of overlapping, or flexible constituency (as in some versions of categorial grammar), and without destroying a transparent link between syntax and semantics. secondly, the reformulation provides a level of description which can act as an intermediate stage between the original grammar and a parsing algorithm. thirdly, it is possible to extend the reformulated grammars with further axioms and deduction rules to provide coverage of syntactic constructions such as coordination which are difficult to encode lexically.
non-constituent coordination: theory and practice. despite the large amount of theoretical work done on non-constituent coordination during the last two decades, many computational systems still treat coordination using adapted parsing strategies, in a similar fashion to the sysconj system developed for atns. this paper reviews the theoretical literature, and shows why many of the theoretical accounts actually have worse coverage than accounts based on processing. finally, it shows how processing accounts can be described formally and declaratively in terms of dynamic grammars.
a matrix representation of the inflectional forms of arabic words: a study of co-occurrence patterns. a proposed "matrix" method for the representation of the inflectional paradigms of arabic words is presented. this representation results in a classification of arabic words into a tree structure (fig(1)) whose leaves represent unique conjugational or derivational paradigms, each represented in the proposed "matrix" form.a study of about 2,500 stems from a high frequency arabic wordlist due to landau <1> has revealed a systematic set of co-occurrence patterns for the enclitic pronouns of arabic verbs and for the possessive pronouns attached to arabic nouns. each co-occurrence pattern represents a subcategorization frame that reflects the underlying semantic relationship.the key feature that distinguishes these semantic patterns has been observed to be whether the attached suffixes relate to the animate or inanimate. in some cases for verbs, the number of the subject is also a significant feature. these semantic features also extend to non-attached subjects and objects (for verbs) and to possessive noun complements (for nouns). therefore the semantic classes presented in this paper also assist in syntactic/semantic analysis.the first application that was developed, based upon the proposed representation is a stem-based arabic morphological analyser, from which a spell checker (on a ps/2 microcomputer) emerged as a by-product. currently, the system is being used to interact with an arabic syntactic parser and there are plans to use it in a machine assisted translation system.
incremental interpretation: applications, theory, and relationship to dynamic semantics. why should computers interpret language incrementally? in recent years psycholinguistic evidence for incremental interpretation has become more and more compelling, suggesting that humans perform semantic interpretation before constituent boundaries, possibly word by word. however, possible computational applications have received less attention. in this paper we consider various potential applications, in particular graphical interaction and dialogue. we then review the theoretical and computational tools available for mapping from fragments of sentences to fully scoped semantic representations. finally, we tease apart the relationship between dynamic semantics and incremental interpretation.
a methodology for terminology-based knowledge acquisition and integration. in this paper we propose an integrated knowledge management system in which terminology-based knowledge acquisition, knowledge integration, and xml-based knowledge retrieval are combined using tag information and ontology management tools. the main objective of the system is to facilitate knowledge acquisition through query answering against xml-based documents in the domain of molecular biology. our system integrates automatic term recognition, term variation management, context-based automatic term clustering, ontology-based inference, and intelligent tag information retrieval. tag-based retrieval is implemented through interval operations, which prove to be a powerful means for textual mining and knowledge acquisition. the aim is to provide efficient access to heterogeneous biological textual data and databases, enabling users to integrate a wide range of textual and non-textual resources effortlessly.
the parsody system: automatic prediction of prosodic boundaries for text-to-speech. as commercial text-to-speech systems move above the word level to the sentence level, the prediction of the correct prosodic informations becomes a significant factor in the perceived naturalness of the synthesised speech.this article reports on "parsody", an experimental system which combines a partial parser with a prosodic marking component to predict the location and relative strength of prosodic boundaries in text.
multitale: linking medical concepts by means of frames. in this paper multitale, a system for the semantic tagging of medical neurosurgical texts and for the semi-automatic expansion of the medical lexicon, will be presented. given the textual information explosion (in particular in, though not restricted to, specialized domains) there is an urgent need for tools enabling to exploit the information available in natural language texts. multitale has been devised therefore primarily with the aim to make explicit semantic information in medical texts, which should lead to more refined information retrieval results. by making "educated guesses" the system moreover has a possibility to expand its own lexicon of medical terms so to be able to cope with new texts.
hierarchical lexical structure and interpretive mapping in machine translation. large-scale knowledge-based machine translation requires significant amounts of lexical knowledge in order to map syntactic structures to conceptual structures. this paper presents a framework in which lexical knowledge is separated into different levels of representation, which are arranged in a hierarchical model based on principles of knowledge representation and lexical semantics. the proposed methodology is language-independent, and has been used to organize lexical knowledge for both english and japanese.
application of analogical modelling to example based machine translation. this paper describes a self-modelling, incremental algorithm for learning translation rules from existing bilingual corpora. the notions of supracontext and subcontext are extended to encompass bilingual information through simultaneous analogy on both source and target sentences and juxtaposition of corresponding results. analogical modelling is performed during the learning phase and translation patterns are projected in a multi-dimensional analogical network. the proposed framework was evaluated on a small training corpus providing promising results. suggestions to improve system performance are this kind of analysis unquestionably leads to more computationally expensive and difficult to obtain systems. our approach consists in a fully modular analogical framework, which can cope with lack of resources, and will perform even better when these are available.
tulips-2 - natural language learning system. the learning of a natural language is considered to be an important aspect of man-machine communication in human language. the methods of the russian language knowledge representation and acquisition implemented in the experimental under-standing system tulips-2 are described. these methods provides for understanding utterances that contain words and structures unknown to the system wherther they are grammatical or erroneous items, or the user's speech peculiarities.
an agreement corrector for russian. the paper describes an application-oriented system that corrects agreement errors. in order to correct a sentence with such errors, an extended morphological structure is created which contains various grammatical forms of the words used in the sentence. for this structure the bottom-up parsing is performed, and syntactic structures are found that contain minimal number of changes in comparison with the original sentence. experiments with real sentences have shown promising results.
identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution. we present a supervised learning approach to identification of anaphoric and non-anaphoric noun phrases and show how such information can be incorporated into a coreference resolution system. the resulting system outperforms the best muc-6 and muc-7 coreference resolution systems on the corresponding muc coreference data sets, obtaining f-measures of 66.2 and 64.0, respectively.
expressive power of grammatical formalisms. we propose formalisms and concepts which allow to make precise the arguments in controversies over the adequacy of competing models of language, and over their formal equivalence.
learning how to answer questions using trivia games. in this paper we examine a sentence comprehension task: given a question, and an extended sentence known to answer that question, the goal is to extract the short answer to the question. as an initial solution, a novel robust statistical model is presented which combines the semantics of the expected answer with the expected context within which the answer will be found. two distinct trivia game databases, with no additional annotation, are used to train and test the model.
an integrated model for anaphora resolution. the paper discusses a new knowledge-based and sublanguage-oriented model for anaphora resolution, which integrates syntactic, semantic, discourse, domain and heuristical knowledge for the sublanguage of computer science. special attention is paid to a new approach for tracking the center throughout a discourse segment, which plays an important role in proposing the most likely antecedent to the anaphor in case of ambiguity.
learning mechanism in machine translation system "pivot". nec's machine translation system "pivot" provides analysis editing functions. the user can interactively correct errors in analysis results, such as dependency and case. however, without a learning mechanism, the user must correct similar dependency errors several times. we discuss the learning mechanism to utilize dependency and case information specified by the user. we compare four types of matching methods by simulation and show non-restricted best matching is the most effective.
discourse structures for text generation. text generation programs need to be designed around a theory of text organization. this paper introduces rhetorical structure theory, a theory of text structure in which each region of text has a central nuclear part and a number of satellites related to it. a natural text is analyzed as an example, the mechanisms of the theory are identified, and their formalization is discussed. in a comparison, rhetorical structure theory is found to be more comprehensive and more informative about text function than the text organization parts of previous text generation systems.
an overview of the edr electronic dictionary and the current status of its utilization. in this paper we present the specification and the structure of edr electronic dictionary which was developed in a nine-year project. the first version of edr dictionary (v1.0) and its revised version (vi.5) are already released and are now utilized at many sites for both academic and commercial purposes. we also describe the current status how the edr dictionary is utilized. finally we will give the outline of the new r&d project which edr will launch in fiscal 1996.