waashk/dblp huggingface dataset:
preferred argument structure for discourse understanding. the main purpose of communication is to exchange information. any discourse understanding model should be able to process the flow of information throughout the entire text. according to du bois (1987)'s studies of information flow in discourse across a number of languages, information distribution among argument positions in clauses is by no means random, but certain grammatical patterns tend to recur consistently. he thus formulated a preferred argument structure (pas) for the preferential structural configurations of arguments. in our examination of chinese narrative discourse, the language also displays pas, yet the chinese pas challenges the universality of the one du bois proposed. based on the quantity and distribution of lexical arguments and new referents across grammatical roles in discourse, it is realized that chinese pas also maintains one new argument at most within a basic information processing unit. since new referents in chinese have to be encoded in full np form, it is thus less likely to have more than one lexical argument within a clause. moreover, this single new argument appears preferentially in the o role, rather than the a and s roles du bois's pas formulates.since the structure of information flow has a corresponding grammatical patterning, both grammatical and pramatic processing can be carried out simultaneously, in that the information status of an argument can be identified by virtue of grammatical analysis. although pas is neither universal nor categorical, it can function in a discourse understanding model as heuristic device to process the information structure of a connected spoken discourse.
a phonological knowledge base system using unification-based formalism - a case study of korean phonology. this paper describes the framework of a korean phonological knowledge base system using the unification based grammar formalism: korean phonology structure grammar (kpsg). the approach of kpsg provides an explicit development model for constructing a computational phonological system: speech recognition and synthesis system. we show that the proposed approach is more describable than other approaches such as those employing a traditional generative phonological approach.
nara: a two-way simultaneous interpretation system between korean and japanese - a methodological study. this paper presents a new computing model for constructing a two-way simultaneous interpretation system between korean and japanese. we also propose several methodological approaches to the construction of a two-way simultaneous interpretation system, and realize the two-way interpreting process as a model unifying both linguistic competence and linguistic performance. the model is verified theoretically and through actual applications.we are deeply grateful to prof. h. yamada for his encouragement. we would like to thank dr. a. adachi and dr. k. hashida, for many stimulating discussions and for detailed comments, and mr. y. shirai and mr. i. fujishiro for suggestions to improve the paper.
empirical estimates of adaptation: the chance of two noriegas is closer to p/2 than p2. repetition is very common. adaptive language models, which allow probabilities to change or adapt after seeing just a few words of a text, were introduced in speech recognition to account for text cohesion. suppose a document mentions noriega once. what is the chance that he will be mentioned again? if the first instance has probability p, then under standard (bag-of-words) independence assumptions, two instances ought to have probability p2, but we find the probability is actually closer to p/2. the first mention of a word obviously depends on frequency, but surprisingly, the second does not. adaptation depends more on lexical content than frequency; there is more adaptation for content words (proper nouns, technical terminology and good keywords for information retrieval), and less adaptation for function words, cliches and ordinary first names.
categorial grammars for strata of non-cf languages and their parsers. we introduce a generalization of categorial grammar extending its descriptive power, and a simple model of categorial grammar parser. both tools can be adjusted to particular strata of languages via restricting grammatical or computational complexity.
explaining away ambiguity: learning verb selectional preference with bayesian networks. this paper presents a bayesian model for unsupervised learning of verb selectional preferences. for each verb the model creates a bayesian network whose architecture is determined by the lexical hicrarchy of wordnet and whose parameters are estimated from a list of verb-object pairs found from a corpus. "explaining away", a well-known property of bayesian networks, helps the model deal in a natural fashion with word sense ambiguity in the training data. on a word sense disambiguation test our model performed better than other state of the art systems for unsupervised learning of selectional preferences. computational complexity problems, ways of improving this approach and methods for implementing "explaining away" in other graphical frameworks are discussed.
knowledge extraction from texts by sintesi. in this paper we present sintesi, a system for the knowledge extraction from italian inputs, currently under development in our research centre. it is used on short descriptive diagnostic texts, in order to summarise their technical content and to build a knowledge base on faults. often in these texts complex linguistic constructions like conjunctions, negations, ellipsis and anaphorae are involved. the presence of extragrammaticalities and of implicit knowledge is also frequent, especially because of the use of a sublanguage. sintesi extracts the diagnostic information by performing a full text analysis; it is based on a semantics driven approach integrated by a general syntactic module and it is able to cope with the complexity of the (sub)language, maintaining both accuracy and robustness. currently the system has been tested on about 1.000 texts and by a few users; in the near future it will be used by dozens of users every day.
a class-based probabilistic approach to structural disambiguation. knowledge of which words are able to fill particular argument slots of a predicate can be used for structural disambiguation. this paper describes a proposal for acquiring such knowledge, and in line with much of the recent work in this area, a probabilistic approach is taken. we develop a novel way of using a semantic hierarchy to estimate the probabilities, and demonstrate the general approach using a prepositional phrase attachment experiment.
uses of c-gpaphs in a prototype for altomatic twislation. this paper presents a prototype, not completely operational, that is intended to use c-graphs in the translation of assemblers. firstly, the formalization of the structure and its principal notions (substructures, classes of substructures, order, etc.) are presented. next section describes the prototype which is bassed on a transformational system as well as on a rewriting system of c-graphs which constitutes the nodes of the transformatinal system. the following part discusses a set of operations on the structure. finally, the implementation in its present state is shown.
semantics of portions and partitive nouns for nlp. this paper describes a system of representation of nouns denoting portions, segments and relative quantities of entities, in order to account for this case of part-whole relationship. the semantics of both constructions denoting portions and nouns used to build them are discussed and eventually formalised in a unification-based formalism (lkb-lrl) in terms of pustejovsky's theory of qualia and jackendoff's conceptual semantics.
evaluating and comparing three text-production techniques. what are the benefits of using natural language generation in an industrial application? we have attempt to answer part of this question with a description of an assessment of three techniques for producing multisentential text: semi-automatic fill-in-the-blank interfacing, automatic linguistic-and-templates hybrid generation, and human writing. this assessment used a black-box methodology, with an independent blind-tested jury that gave different quality levels in relation to a set of criteria. the texts used for the assessment were business reply letters.
a formalism for the structural analysis of dialogues. this paper outlines a formalism for conversational analysis that captures multiple interactional patterns of mixed-initiative and fix the historical skeleton of a dialogue. the formalism, composed by a grammar of dialogues (syntax and semantic component) and a collection of attached scenarios (pragmatic component), is written in prolog and implemented in a program which converses in portugu<u>e</u> se to provide a library service.
a computational theory of the function of clue words in argument understanding. this paper examines the use of clue words in argument dialogues. these are special words and phrases directly indicating the structure of the argument to the hearer. two main conclusions are drawn: 1) clue words can occur in conjunction with coherent transmissions, to reduce processing of the hearer 2) clue words must occur with more complex forms of transmission, to facilitate recognition of the argument structure. interpretation rules to process clues are proposed. in addition, a relationship between use of clues and complexity of processing is suggested for the case of exceptional transmission strategies.
n-gram cluster identification during empirical knowledge representation generation. this paper presents an overview of current research concerning knowledge extraction from technical texts. in particular, the use of empirical techniques during the identification and generation of a semantic representation is considered. a key step is the discovery of useful n-grams and correlations between clusters of these n-grams.
extracting the names of genes and gene products with a hidden markov model. we report the results of a study into the use of a linear interpolating hidden markov model (hmm) for the task of extracting technical terminology from medline abstracts and texts in the molecular-biology domain. this is the first stage in a system that will extract event information for automatically updating biology databases. we trained the hmm entirely with bigrams based on lexical and character features in a relatively small corpus of 100 medline abstracts that were marked-up by domain experts with term classes such as proteins and dna. using cross-validation methods we achieved an f-score of 0.73 and we examine the contribution made by each part of the interpolation model to overcoming data sparseness.
can computers handle adverbs? the adverb is the most complicated, and perhaps also the most interesting part of speech. past research in natural language processing, however, has not dealt seriously with adverbs, though linguists have done significant work on this word class. the current paper draws on this linguistic research to organize an adverbial lexicon which will be useful for information retrieval and natural language processing systems.
conveying implicit content in narrative summaries. one of the key characteristics of any summary is that it must be concise. to achieve this the content of the summary (1) must be focused on the key events, and (2) should leave out any information that the audience can infer on their own. we have recently begun a project on summarizing simple narrative stories. in our approach, we assume that the focus of the story has already been determined and is explicity given in the story's long-term representation; we concentrate instead on how one can plan what inferences an audience will be able to make when they read a summary. our conclusion is that one should think about inferences as following from the audience's recognition of the central concepts in the story's plot, and then plan the textual structure of the summary so as to reinforce that recognition.
parsing and case analysis in tanka. the tanka project seeks to build a model of a technical domain by semi-automatically processing unedited english text that describes this domain. each sentence is parsed and conceptual elements are extracted from the parse. concepts are derived from the case structure of a sentence, and added to a conceptual network that represents knowledge about the domain. the dipett parser has a particularly broad coverage of english syntax; its newest version can also process sentence fragments. the haiku subsystem is responsible for user-assisted semantic interpretation. it contains a case analyzer module that extracts phrases marking concepts from the parse and uses its past processing experience to derive the most likely case realizations of each with almost no a priori semantic knowledge. the user must validate these selections. a key issue in our research is minimizing the number of interactions with the user by intelligently generating the alternatives offered.
towards machine translation using contextual information. a proposal is made for the use of contextual information in the machine translation of japanese and english. this paper describes the use of a context monitor to maintain contextual information dynamically and the augmentation of appropriate features to a semantic network to enable simple inference. the approach taken is that of "best guess" processing with the contextual information being handled with semantic information on a shallow level.
a binding rule for government-binding parsing. in this paper i propose a binding rule for the identification of pronoun and anaphor referents in phrase-structure tress, assuming the general framework of the government-binding theory outlined by chomsky (1981). the binding rule, specified by means of an attribute grammar, is a particular instantiation of the free indexing rule and binding axioms in chomsky's binding theory, with certain empirical and practical advantages. the complexities of the binding rule proposed, as well as that inherent in chomsky's binding theory, are studied, and it is shown that the new rule is more psychologically plausible and computationally efficient than the original theory on which it is based. the fragment of the attribute grammar shown here is part of an english grammar and parser being developed in the prolog and plnlp languages.
lexical disambiguation using simulated annealing. the resolution of lexical ambiguity is important for most natural language processing tasks, and a range of computational techniques have been proposed for its solution. none of these has yet proven effective on a large scale. in this paper, we describe a method for lexical disambiguation of text using the definitions in a machine-readable dictionary together with the technique of simulated annealing. the method operates on complete sentences and attempts to select the optimal combinations of word senses for all the words in the sentence simultaneously. the words in the sentences may be any of the 28,000 headwords in longman's dictionary of contemporary english (ldoce) and are disambiguated relative to the senses given in ldoce. our initial results on a sample set of 50 sentences are comparable to those of other researchers, and the fully automatic method requires no hand-coding of lexical entries, or hand-tagging of text.
the week at a glance - cross-language cross-document information extraction and translation. work on the production of texts in english describing instances of a particular event type from multiple news sources will be described. a system has been developed which extracts events, such as meetings, from texts in english, russian, spanish, and japanese. the extraction is currently carried out using only ontological information. the results of a set of such extractions were combined to produce a table of event instances, date stamped, with links back to the original documents. the original documents can then be summarized and translated by the system on demand.by using techniques from information retrieval, information extraction, summarization, and machine translation, in a multi-lingual environlment, new documents can be produced which provide "at a glance" access to news ell events from multiple sources.the paper concludes with a discussion of the key resources which need to be developed to enhance the accuracy and coverage of the techniques used in our experiment.
a matching technique in example-based machine translation. this paper addresses an important problem in example-based machine translation (embt), namely how to measure similarity between a sentence fragment and a set of stored examples. a new method is proposed that measures similarity according to both surface structure and content. a second contribution is the use of clustering to make retrieval of the best matching example from the database more efficient. results on a large number of test cases from the celex database are presented.
an empirical investigation of the relation between discourse structure and co-reference. we compare the potential of two classes of linear and hierarchical models of discourse to determine co-reference links and resolve anaphors. the comparison uses a corpus of thirty texts, which were manually annotated for co-reference and discourse structure.
frame based recognition of theme continuity. the paper describes a system which determines continuity and shifts in english texts on the basis of sentential themes. the theme object within the thematic component of a sentence is determined and a search is made to associate it with a frame shared with the previous theme or themes. if the theme object cannot be associated directly with one of these frames, interpretive rules are applied to do so indirectly through one of the frames normally associated with the object but not yet with the text.
gate-a general architecture for text engineering. much progress has been made in the provision of reusable data resources for natural language engineering, such as grammars, lexicons, thesauruscs. although a number of projects have addressed the provision of reusable algorithmic resources (or 'tools'), takeup of these resources has been relatively slow. this paper describes gate, a general architecture for text engineering, which is a freely-available system designed to help alleviate the problem.
augmented x'-schemes. the paper presents the embedding of an original parsing strategy for romanian, called segmentation-cohesion-dependency (scd), into chomsky's well-known government and binding (bg) theory. in order to bring closer the scd concepts and techniques to the gb theory, the following questions have had to be dealt with: (1) a specification of the principle of maximal projection (pmp), (2) extending the x'-theory (x - bar) by introdusing augmented x' (ax')-schemes, these ones being obtained by (3) specific constraints imposed on the new shapes of x'-schemes. (4) the ax'-schemes can be represented in terms of a tree (paranthetic) language, whose translation in a logic programming language follows naturally.
grafon: a grapheme-to-phoneme conversion system for duth. we describe a set of modules that together make up a grapheme-to-phoneme coversion system for dutch. modules include a syllabification program, a fast morphological parser, a lexical database, a phonological knowledge base, transliteration rules, and phonological rules. knowledge and procedures were implemented object-orientedly. we contrast grafon to recent pattern recognition and rule-compiler approaches and try to show that the first fails for languages with concatenative compounding (like dutch, german, and scandinavian languages) while the second lacks the flexibility to model different phonological theories. it is claimed that syllables (and not graphemes/phonemes or morphemes) should be central units in a rule-based phonemisation algorithm. furthermore, the architecture of grafon and its user interface make it ideally suited as a rule-testing tool for phonologists.
unsupervised discovery of phonological categories through supervised learning of morphological rules. we describe a case study in the application of symbolic machine learning techniques for the discovery of linguistic rules and categories. a supervised rule induction algorithm is used to learn to predict the correct diminutive suffix given the phonological representation of dutch nouns. the system produces rules which are comparable to rules proposed by linguists. furthermore, in the process of learning this morphological task, the phonemes used are grouped into phonologically relevant categories. we discuss the relevance of our method for linguistics and language technology.
automatic processing of large corpora for the resolution of anaphora references. manual acquisition of semantic constraints in broad domains is very expensive. this paper presents an automatic scheme for collecting statistics on cooccurrence patterns in a large corpus. to a large extent, these statistics reflect semantic constraints and thus are used to disambiguate anaphora references and syntactic ambiguities. the scheme was implemented by gathering statistics on the output of other linguistic tools. an experiment was performed to resolve references of the pronoun "it" in sentences that were randomly selected from the corpus. the results of the experiment show that in most of the cases the cooccurrence statistics indeed reflect the semantic constraints and thus provide a basis for a useful disambiguation tool.
kind types in knowledge representation. this paper describes kind types (kt), a system which uses commonsense knowledge to reason about natural language text. kt encodes some of the knowledge underlying natural language understanding, including category distinctions and descriptions differentiating real-world objects, states and events. it embeds an ontology reflecting the ordinary person's top-level cognitive model of real-world distinctions and a database of prototype descriptions of real-world entities. kt is transportable, empirically-based and constrained for efficient reasoning in ways similar to human reasoning processes.
morphological rule induction for terminology acquisition. we present the identification in corpora of french relational adjectives (radj) such as gazeux (gascous) which is derived from the noun gaz (gas). radj appearing in nominal phrases are interesting for terminology acquisition because they hold a naming function. the derivational rules employed to compute the noun from which has been derived the radj are acquired semi-automatically from a tagged and a lemmatized corpora. these rules are then integrated into a termer which identifies radj thanks to their property of being paraphrasable by a prepositional phrase. radj and compound nouns which include a radj are then quantified, their linguistic precision is measured and their informative status is evaluated thanks to a thesaurus of the domain.
towards automatic extraction of monolingual and bilingual terminology. in this paper, we make use of linguistic knowledge to identify certain noun phrases, both in english and french, which are likely to be terms. we then test and compare different statistical scores to select the "good" ones among the candidate terms, and finally propose a statistical method to build correspondences of multi-words units across languages.