waashk/dblp huggingface dataset:
semiautomatic interactive muitilingual style analysis (simsa). a style checker is a tool which supports authors during the process of writing: certain style markers are analyzed, their values are compared with a given norm, deviations are detected, and recommendations are given to the author. the power of a style checker depends on available tools such as lexica, parser, etc. this paper describes a style checker which will be integrated in a workbench (translator's workbench) and which has access to lexica and parser. the style checker can be used for different languages and for different kinds of text.
incremental parsing and reason maintenance. the purpose of this paper is to compare different ways of adopting reason-maintenance techniques in incremental parsing (and interpretation). a reason-maintenance system supports incremental formation and revision of beliefs. by viewing the construction of partial analyses of a text as analogous to forming beliefs about the meanings of its parts, a relation between parsing and reason maintenance can be conceived. in line with this, reason maintenance can be used for realizing a strong notion of incremental parsing, allowing for revisions of previous analyses. moreover, an assumption-based reason-maintenance system (atms) can be used to support efficient comparisons of (competing) interpretations. the paper argues for an approach which is an extension of chart parsing, but which also can be seen as a system consisting of an inference engine (the parser proper) coupled with a simplified atms.
minimal change and bounded incremental parsing. ideally, the time that an incremental algorithm uses to process a change should be a function of the size of the change rather than, say, the size of the entire current input. based on a formalization of "the set of things changed" by an incremental modification, this paper investigates how and to what extent it is possible to give such a guarantee for a chart-based parsing framework and discusses the general utility of a minimality notion in incremental processing.
prosody and the resolution of pronominal anaphora. in this paper, we investigate the acoustic prosodic marking of demonstrative and personal pronouns in task-oriented dialog. although it has been hypothesized that acoustic marking affects pronoun resolution, we find that the prosodic information extracted from the data is not sufficient to predict antecedent type reliably. inter-speaker variation accounts for much of the prosodic variation that we find in our data. we conclude that prosodic cues should be handled with care in robust, speaker-independent dialog systems.
chinese word segmentation based on maximum matching and word binding force. a chinese word segmentation algorithm based on forward maximum matching and word binding force is proposed in this paper. this algorithm plays a key role in post-processing the output of a character or speech recognizer in determining the proper word sequence corresponding to an input line of character images or a speech waveform. to support this algorithm, a text corpus of over 63 millions characters is employed to enrich an 80,000-words lexicon in terms of its word entries and word binding forces. as it stands now, given an input line of text, the word segmentor can process on the average 210,000 characters per second when running on an ibm risc system/6000 3bt workstation with a correct word identification rate of 99.74%.
machine translation for monolinguals. we describe sister machine translation prototypes, ntran, an english to japanese system developed at umist, and aidtrans, japanese to english, at sheffield, both designed for use by an english monolingual. aidtrans uses extensive and sophisticated collocational analysis radically to reduce the need for conventional post-editing. ntran offers interactive query at three stages: on-line dictionary update, syntactic disambiguation, and japanese lexical selection. the second of these is described and illustrated in particular detail, and the underlying philosophy of monolingual interaction discussed.
machine learing of morphological rules by generalization and analogy. this paper describes an experimental procedure for the inductive automated learning of morphological rules from examples. at first an outline of the problem is given. then a formalism for the representation of morphological rules is defined. this formalism is used by the automated procedure, whose anatomy is subsequently presented. finally the performance of the system is evaluated and the most important unsolved problems are discussed.
massive disambiguation of large text corpora with flexible categorial grammar. a new method of automatic lexical disambiguation of big texts is described, using recent proof-theoretical results from the theory of categorial grammar.
dynamic lexical acquisition in chinese sentence analysis. dynamic lexical acquisition is a procedure where the lexicon of an nlp system is updated automatically during sentence analysis. in our system, new words and new attributes are proposed online according to the context of each sentence, and then get accepted or rejected during syntactic analysis. the accepted lexical information is stored in an auxiliary lexicon which can be used in conjunction with the existing dictionary in subsequent processing. in this way, we are able to process sentences with an incomplete lexicon and fill in the missing info without the need of human editing. as the auxiliary lexicons are corpus-based, domain-specific dictionaries can be created automatically by combining the existing dictionary with different auxiliary lexicons. evaluation shows that this mechanism significantly improves the coverage of our parser.
disambiguation and language acquisition through th phrasal lexicon. the phrasal approach to language processing emphasizes the role of the lexicon as a knowledge source. rather than maintaining a single generic lexical entry for each word e.g., take, the lexicon contains many phrases, e.g., take on, take to the streets, take to swimming, take over, etc. although this approach proves effective in parsing and in generation, there are two acute problems which still require solutions. first, due to the huge size of the phrasal lexicon, especially when considering subtle meanings and idiosyneratic behavior of phrases, encoding of lexical entries cannot be done manually. thus, phrase acquisition must be employed to construct the lexicon. second, when a set of phrases is morpho-syntactically equivalent, disambiguation must be performed by semantic means. these problems are addressed in the program rina.
figuring out most plausible interpretation from spatial descriptions. the problem we want to handle in this paper is vagueness. a notion of space, which we basically have, plays an important part in the faculty of thinking and speech. in this paper, we concentrate on a particular class of spatial descriptions, namely descriptions about positional relations on a two-dimensional space. a theoretical device we present in this paper is called the potential model. the potential model provides a means for accumulating from fragmentary information. it is possible to derive maximally plausible interpretation from a chunk of information accumulated in the model. when new information is given, the potential model is modefied so that that new information is taken into account. as a result, the interpretations with maximal plausibility may change. a program called sprint(spatial relation in-terpreter) reflecting our theory is in the way of construction.
tagging for learning: collecting thematic relations from corpus. recent work in text analysis has suggested that data on words that frequently occur together reveal important information about text content. co-occurrence relations can serve two main purposes in language processing. first, the statistics of co-occurrence have been shown to produce accurate results in syntactic analysis. second, the way that words appear together can help in assigning thematic roles in semantic interpretation. this paper discusses a method for collecting co-occurrence data, acquiring lexical relations from the data, and applying these relations to semantic analysis.
reconstructing spatial image from natural language texts. this paper describes the understanding process of the spatial descriptions in japanese. in order to understand the described world, the authors try to reconstruct the geometric model of the global scene from the scenic descriptions drawing a space. it is done by an experimental computer program sprint, which takes natural language texts and produces a model of the described world. to reconstruct the model, the authors extract the qualitative spatial constraints from the text, and represent them as the numerical constraints on the spatial attributes of the eutities. this makes it possible to express the vagueness of the spatial concepts and to derive the maximally plausible interpretation from a chunk of information accumulated as the constraints. the interpretation reflects the temporary belief about the world.
morphological analysis and synthesis by automated discovery and acquisition of linguistic rules. this paper describes a rule-based machine learning approach to morphological processing in the system called xmas. xmas discovers and acquires linguistic rules from examples of morphological combinations and accomplishes the morphological analysis and synthesis by applying the rules. this approach is independent of languages, saves time and effort for development and maintenance, and takes small lexicon space. a korean version of xmas is effectively working in the english-korean machine translation system kshalt.
machine translation by interaction between paraphraser and transfer. a machine translation model has been proposed where an input is translated through both source-language and target-language paraphrasing processes. we have implemented our prototype model for the japanese-chinese language pair. this paper. describes our core idea of translation, where a source language paraphraser and a language transfer cooperates in translation by exchanging information about the source input.
chinese syntactic parsing based on extended glr parsing algorithm with pcfg*. this paper presents an extended glr parsing algorithm with grammar pcfg* that is based on tomita's glr parsing algorithm and extends it further. we also define a new grammar---pcfg* that is based on pcfg and assigns not only probability but also frequency associated with each rule. so our syntactic parsing system is implemented based on rule-based approach and statistics approach. furthermore our experiments are executed in two fields: chinese base noun phrase identification and full syntactic parsing. and the results of these two fields are compared from three ways. the experiments prove that the extended glr parsing algorithm with pcfg* is an efficient parsing method and a straightforward way to combine statistical property with rules. the experiment results of these two fields are presented in this paper.
acquisition of phrase-level bilingual correspondence using dependency structure. this paper describes a method to find phrase-level translation patterns from parallel corpora by applying dependency structure analysis. we use statistical dependency parsers to determine dependency relations between base phrases in a sentence. our method is tested with a business expression corpus containing 10000 english-japanese sentence pairs and achieved approximately 90% accuracy in extracting bilingual correspondences. the result shows that the use of dependency relation helps to acquire interesting translation patterns.
paraphrasing of chinese utterances. one of the key issues in spoken language translation is how to deal with unrestricted expressions in spontaneous utterances. this research is centered on the development of a chinese paraphraser that automatically paraphrases utterances prior to transfer in chinese-japanese spoken language translation. in this paper, a pattern-based approach to paraphrasing is proposed for which only morphological analysis is required. in addition, a pattern construction method is described through which paraphrasing patterns can be efficiently learned from a paraphrase corpus and human experience. using the implemented paraphraser and the obtained patterns, a paraphrasing experiment was conducted and the results were evaluated.
predicting noun-phrase surface forms using contextual information. we propose a context-sensitive method to predict noun-phrases in the next utterance of a telephone inquiry dialogue. first, information about the utterance type and the discourse entities of the next utterance is grasped using a dialogue interpretation model. second, a domain-dependent knowledge base for noun-phrase usage is developed, focusing on the dialogue situations in context. finally, we propose a strategy to make a set of the appropriate expressions in the next utterance, using the information and the knowledge base. this set of expressions is used to select the correct candidate from the speech recognition output. this paper examines some of the processes creating sets of polite expressions, deicti&cacute; expressions, and compound noun phrases, which are common in telephone inquiry dialogue.
collocational analysis in japanese text input. this paper proposes a new disambiguation method for japanese text input. this method evaluates candidate sentences by measuring the number of word co-occurrence patterns (wcp) included in the candidate sentences. an automatic wcp extraction method is also developed. an extraction experiment using the example sentences from dictionaries confirms that wcp can be collected automatically with an accuracy of 98.7% using syntactic analysis and some heuristic rules to eliminate erroneous extraction. using this method, about 305,000 sets of wcp are collected. a co-occurrence pattern matrix with semantic categories is built based on these wcp, using this matrix, the mean number of candidate sentences in kana-to-kanji translation is reduced to about 1/10 of those from existing morphological methods.
complex features in description of chinese language. in this paper, the similarity of "multi---value label function" and "complex features" is discussed. the author especially emphasizes the necessity of complex features for description of chinese language.
local context templates for chinese constituent boundary prediction. in this paper, we proposed a shallow syntactic knowledge description: constituent boundary representation and its simple and efficient prediction algorithm, based on different local context templates learned from the annotated corpus. an open test on 2780 chinese real text sentences showed the satisfying results: 94% (92%) precision for the words with multiple (single) boundary tag output.
the semantic representation of spatial configurations: a conceptual motivation for generation in machine translation. this paper deals with the automatic translation of prepositions, which are highly polysemous. moreover, the same real situation is often expressed by different prepositions in different languages. we proceed from the hypothesis that different usage patterns are due to different conceptualizations of the same real situation. following cognitive principles of spatial conceptualization, we design a semantic interpretation process for spatial relations in which our translation system uses semantic features derived from a semantic sort hierarchy. thus we can differentiate subtle distinctions between spatially significant configurations.
an efficient syntactic tagging tool for corpora. the tree bank is an important resoures for mt and linguistics researches, but it requires that large number of sentences be annotated with syntactic information. it is time consuming and troublesome, and difficult to keep consistency, if annotation is done manually. in this paper, we presented a new technique for the semi-automatic tagging of chinese text. the system takes as input chinese text, and outputs the syntactically tagged sentence(dependency tree). we use dependency grammar and employ a stack based shift/ reduce context-dependent parser as the tagging mechanism. the system works in human-machine cooperative way, in which the machine can acquire tagging rules from human intervention. the automation level can be improved step by step by accumulating rules during annotation. in addition, good consistency of tagging is guaranteed.
the chinese aspect system and its semantic interpretation. motivated by a systematic representation of the chinese aspect forms that explores their intrinsic semantics and temporal logical relations, we are constructing a chinese aspect system network based on systemic functional grammar and implemented using the multilingual generator kpml. in this paper, we introduce the basic simple primary aspect forms and a set of secondary types of the unmarked-durative aspect in our chinese aspect system, describe the semantic temporal relations of complex aspect in terms of temporal logic theories, and propose principled semantic conditions for aspect combination. finally, we give a brief explanation of the system implementation.
a linear least squares fit mapping method for information retrieval from natural language texts. this paper describes a unique method for mapping natural language texts to canonical terms that identify the contents of the texts. this method learns empirical associations between free-form texts and canonical terms from human-assigned matches and determines a linear least squares fit (llsf) mapping function which represents weighted connections between words in the texts and the canonical terms. the mapping function enables us to project an arbitrary text to the canonical term space where the "transformed" text is compared with the terms, and similarity scores are obtained which quantify the relevance between the the text and the terms. this approach has superior power to discover synonyms or related terms and to preserve the context sensitivity of the mapping. we achieved a rate of 84% in both the recall and the precision with a testing set of 6,913 texts, outperforming other techniques including string matching (15%), morphological parsing (17%) and statistical weighting (21%).
considerations of linking wordnet with mrd. this paper introduces a bilingual mrd (english-chinese ldoce) to help with the construction of a chinese wordnet. considerable linking strategies are discussed and proper translations are attached to 28,388 noun synsets and 10,380 verb synsets of wn 1.7 automatically. the steady precision (92~94%) shows the corresponding headwords and matching keywords provide considerable guarantee for linking. the chinese phrases need to be processed further to match the correct synset due to the fine-grained senses of wordnet.
use of heuristic knowledge in chinese language analysis. this paper describes an analysis method which uses heuristic knowledge to find local syntactic structures of chinese sentences. we call it a preprocessing, because we use it before we do global syntactic structure analysis (1) of the input sentence. our purpose is to guide the global analysis through the search space, to avoid unnecessary computation.to realize this, we use a set of special words that appear in commonly used patterns in chinese. we call them "characteristic words". they enable us to pick out fragments that might figure in the syntactic structure of the sentence. knowledge concerning the use of characteristic words enables us to rate alternative fragments, according to pattern statistics, fragment length, distance between characteristic words, and so on. the preprocessing system proposes to the global analysis level a most "likely" partial structure. in case this choice is rejected, backtracking looks for a second choice, and so on.for our system, we use 200 characteristic words. their rules are written by 101 automata. we tested them against 120 sentences taken from a chinese physics text book. for this limited set, correct partial structures were proposed as first choice for 94% of sentences. allowing a 2nd choice, the score is 98%, with a 3rd choice, the score is 100%.
automatic acquisition of domain knowledge for information extraction. in developing an information extraction (ie) system for a new class of events or relations, one of the major tasks is identifying the many ways in which these events or relations may be expressed in text. this has generally involved the manual analysis and, in some cases, the annotation of large quantities of text involving these events. this paper presents an alternative approach, based on an automatic discovery procedure, exdisco, which identifies a set of relevant documents and a set of event patterns from un-annotaled text, starting from a small set of "seed patterns." we evaluate exdisco by comparing the performance of discovered patterns against that of manually constructed systems on actual extraction tasks.
the power of words in message planning. before engaging in a conversation, a message must be planned. while there are many ways to perform this task, i believe that people do this in the following way, in particular if the message is going to be long: first an outline is planned (global, or skeleton planning), which is then filled in with details (local planning, elaboration). planning proceeds thus from general to specific (breadth first), that is, sentences are planned incremetally by gradual refinement of some abstract thought rather than in one go (one-shot process) where every element is planned down to its last details.while global planning is largely language independent, local planning can be language dependent: the dictionary acts a mediator, interfacing language and thought. given the fact that words can be used to specify non linguistic thought, there is feedback from the lexical to the conceptual component. this being so, dictionaries may play a fundamental role in guiding and potentially modifying non linguistic thought. if my view is correct, this could have implications on the design of generation architectures: instead of separating message planning and realization, viewing the process as being strictly sequential, we could allow for feedback loops (interleaved process), whereby the linguistic component could feed back to the conceptual component.
unsupervised learning of generalized names. we present an algorithm, nomen, for learning generalized names in text. examples of these are names of diseases and infectious agents, such as bacteria and viruses. these names exhibit certain properties that make their identification more complex than that of regular proper names, nomen uses a novel form of bootstrapping to grow sets of textual instances and of their contextual patterns. the algorithm makes use of competing evidence to boost the learning of several categories of names simultaneously. we present results of the algorithm on a large corpus. we also investigate the relative merits of several evaluation strategies.
an automatic evaluation method for localization oriented lexicalised ebmt system. to help developing a localization oriented ebmt system, an automatic machine translation evaluation method is implemented which adopts edit distance, cosine correlation and dice coefficient as criteria. experiment shows that the evaluation method distinguishes well between "good" translations and "bad" ones. to prove that the method is consistent with human evaluation, 6 mt systems are scored and compared. theoretical analysis is made to validate the experimental results. correlation coefficient and significance tests at 0.01 level are made to ensure the reliability of the results. linear regression equations are calculated to map the automatic scoring results to human scorings.