Knowledge and language

Xem 1-20 trên 515 kết quả Knowledge and language
  • We present UWN, a large multilingual lexical knowledge base that describes the meanings and relationships of words in over 200 languages. This paper explains how link prediction, information integration and taxonomy induction methods have been used to build UWN based on WordNet and extend it with millions of named entities from Wikipedia. We additionally introduce extensions to cover lexical relationships, frame-semantic knowledge, and language data. An online interface provides human access to the data, while a software API enables applications to look up over 16 million words and names.

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  • In order to represent speech acts, in a multi-agent context, we choose a knowledge representation based on the modal logic of knowledge KT4 which is defined by Sato. Such a formalism allows us to reason about knowledge and represent knowledge about knowledge, the notions of truth value and of definite reference.

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  • Linguistic knowledge usable for machine translation is always imperfect. We cannot be free from the uncertainty of knowledge we have for machine translation. Especially at the transfer stage of machine translation, the selection of target language expression is rather subjective and optional. Therefore the linguistic contents of machine translation system always fluctuate, and make gradual progress. The system should be designed to allow such constant change and improvements.

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  • This volume descibes, in up-to-date terminology and authoritative interpretation, the field of neurolinguistics, the science concerned with the neural mechanisms underlying the comprehension, production and abstract knowledge of spoken, signed or written language.

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  • Acquiring Knowledge and Skills 1. Learning experiences that engage students in active learning, build on prior knowledge and experiences, and develop conceptual and procedural understanding, along with student independence. Variety of Instructor Roles 2. Teachers who use a variety of teaching roles (e.g., direct instruction, facilitating, modeling, coaching, reflecting, and guiding observing), and adapt these as appropriate for different purposes of instruction and student needs. Multiple Student Roles 3. Opportunities to learn through a variety of roles (e.g.

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  • This guide was developed to assist teachers in successfully implementing the Michigan Merit Curriculum. The identified content expectations and guidelines provide a useful framework for designing curriculum, assessments and relevant learning experiences for students. Through the collaborative efforts of Governor Jennifer M.

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  • What are human languages, such that they can be acquired and used as they are? This class surveys some of the most important and recent approaches to this question, breaking the problem up along traditional lines. In spoken languages, what are the basic speech sounds? How are these sounds articulated and combined? What are the basic units of meaning? How are the basic units of meaning combined into complex phrases? How are these complexes interpreted? These questions are surprisingly hard! This introductory survey can only briefly touch on each one....

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  • Ebook Spectrum Language Arts Grade 4 includes focused practice for language arts mastery such as grammar and usage, parts of speech and sentence types, vocabulary acquisition and usage, and a writer's guide. Spectrum(R) Reading workbooks contain focused practice for reading comprehension, including letters and sounds, word recognition, integration of knowledge and ideas, key ideas and details, main idea, story structure, theme, and summarization. Each lesson features an illustrated story followed by exercise in comprehension.

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  • The essays collected in this volume represent work carried out over a period of more than ten years on a variety of problems in artificial intelligence, the philosophy of mind and language, and natural-language semantics, addressed from a perspective that takes as central the use of formal logic and the explicit representation of knowledge.

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  • We present experiments with part-ofspeech tagging for Bulgarian, a Slavic language with rich inflectional and derivational morphology. Unlike most previous work, which has used a small number of grammatical categories, we work with 680 morpho-syntactic tags. We combine a large morphological lexicon with prior linguistic knowledge and guided learning from a POS-annotated corpus, achieving accuracy of 97.98%, which is a significant improvement over the state-of-the-art for Bulgarian.

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  • The growing availability of spoken language corpora presents new opportunities for enriching the methodologies of speech and language therapy. In this paper, we present a novel approach for constructing speech motor exercises, based on linguistic knowledge extracted from spoken language corpora. In our study with the Dutch Spoken Corpus, syllabic inventories were obtained by means of automatic syllabification of the spoken language data.

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  • This demonstration presents the LinGO Grammar Matrix grammar customization system: a repository of distilled linguistic knowledge and a web-based service which elicits a typological description of a language from the user and yields a customized grammar fragment ready for sustained development into a broad-coverage grammar. We describe the implementation of this repository with an emphasis on how the information is made available to users, including in-browser testing capabilities.

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  • Understanding language requires both linguistic knowledge and knowledge about how the world works, also known as common-sense knowledge. We attempt to characterize the kinds of common-sense knowledge most often involved in recognizing textual entailments.

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  • Language models based on word surface forms only are unable to benefit from available linguistic knowledge, and tend to suffer from poor estimates for rare features. We propose an approach to overcome these two limitations. We use factored features that can flexibly capture linguistic regularities, and we adopt confidence-weighted learning, a form of discriminative online learning that can better take advantage of a heavy tail of rare features.

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  • In the field of knowledge based systems for natural language processing, one of the most challenging aims is to use parts of an existing knowledge base for different domains and/or different tasks. We support the point that this problem can only be solved by using adequate metainformation about the content and structuring principles of the representational systems concerned. One of the prerequisites in this respect is the transparency of modelling decisions.

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  • The nature and amount of information needed for learning a natural language, and the underlying mechanisms involved in this process, are the subject of much debate: is it possible to learn a language from usage data only, or some sort of innate knowledge and/or bias is needed to boost the process? This is a topic of interest to (psycho)linguists who study human language acquisition, as well as computational linguists who develop the knowledge sources necessary for largescale natural language processing systems. ...

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  • We have witnessed signi cant progress in NLP applications such as information extraction IE, summarization, machine translation, cross-lingual information retrieval CLIR, etc. The progress will be accelerated by advances in speech technology, which not only enables us to interact with systems via speech but also to store and retrieve texts input via speech.

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  • it is widely reco~nlzed that the process of understandln~ natural language texts cannot be accomplished w i t h o u t accessin~ mundane Knowledge a b o u t the w o r l d [2, 4, 6, 7]. That is, in order to resolve ambiguities, form expectations, and make causal connections between events, we must make use of all sorts of episodic, stereotypic and factual knowledge. In this p a p e r , we are concerned with the way functional knowledge of objects, and associations between objects can be exploited in an understandln~ system. ...

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  • A computer system is being developed to handle the acquisition, representation, and use of linguistic knowledge. The computer system is rule-based and utilizes a semantic network for knowledge storage and representation. In order to facilitate the interaction between user and system, input of linguistic knowledge and computer responses are in natural language. Knowledge of various types can be entered and utilized: syntactic and semantic; assertions and rules.

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  • This paper describes a general approach to the design of natural language interfaces that has evolved during the development of DATALOG, an English database query system based on Cascaded ATN grammar. By providing separate representation schemes for linguistic knowledge, general world knowledge, and application domain knowledge, DATALOG achieves a high degree of portability and extendability.

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