Semantic consistency

Xem 1-20 trên 42 kết quả Semantic consistency
  • We introduce a first-order language for semantic underspecification that we call Constraint Language for Lambda-Structures (CLLS). A Astructure can be considered as a A-term up to consistent renaming of bound variables (aequality); a constraint of CLLS is an underspecified description of a A-structure. CLLS solves a capturing problem omnipresent in underspecified scope representations. CLLS features constraints for dominance, lambda binding, parallelism, and anaphoric links. Based on CLLS we present a simple, integrated, and underspecified treatment of scope, parallelism, and anaphora. ...

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  • Can a realist model t h e o r y of natural language be computationally plausible? Or, t o p u t i t another way, is the view of linguistic meaning as a relation between expressions of a natural language and things (objects, properties, etc.) in the world, as opposed to a relation between expressions and procedures in the head. consistent with a computational approach to understanding natural language?

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  • During thc past two decades, much work in linguistics has focused on sentences as minimal units of communication, and the project of rigorously characterizing the structure of sentences in natural language has met with some succcss. Not surprisingly, however, sentcnce grammars have contributed little to the analysis of discourse, Human discourse consists not just of words in sequences, hut of words in sequences directed by a speaker to an addressee, used to represent situations and to reveal intentions.

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  • We propose models for semantic orientations of phrases as well as classification methods based on the models. Although each phrase consists of multiple words, the semantic orientation of the phrase is not a mere sum of the orientations of the component words. Some words can invert the orientation. In order to capture the property of such phrases, we introduce latent variables into the models. Through experiments, we show that the proposed latent variable models work well in the classification of semantic orientations of phrases and achieved nearly 82% classification accuracy. ...

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  • Semantic Role Labeling (SRL) consists of, given a sentence, detecting basic event structures such as “who” did “what” to “whom”, “when” and “where”. From a linguistic point of view, a key component of the task corresponds to identifying the semantic arguments filling the roles of the sentence predicates. Typical predicate semantic arguments include Agent, Patient, and Instrument, but semantic roles may also be found as adjuncts (e.g., Locative, Temporal, Manner, and Cause).

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  • A hybrid convolution tree kernel is proposed in this paper to effectively model syntactic structures for semantic role labeling (SRL). The hybrid kernel consists of two individual convolution kernels: a Path kernel, which captures predicateargument link features, and a Constituent Structure kernel, which captures the syntactic structure features of arguments. Evaluation on the datasets of CoNLL2005 SRL shared task shows that the novel hybrid convolution tree kernel outperforms the previous tree kernels.

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  • We describe a novel neural network architecture for the problem of semantic role labeling. Many current solutions are complicated, consist of several stages and handbuilt features, and are too slow to be applied as part of real applications that require such semantic labels, partly because of their use of a syntactic parser (Pradhan et al., 2004; Gildea and Jurafsky, 2002). Our method instead learns a direct mapping from source sentence to semantic tags for a given predicate without the aid of a parser or a chunker. ...

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  • Suppose we have a feature system, and we wish to add default values in a well-defined way. We might start with Kasper-Rounds logic, and use Reiter's example to form it into a default logic. Giving a node a default value would be equivalent to saying "if it is consistent for this node to have that value, then it does." Then we could use default theories to describe feature structures. The particular feature structure described would be the structure that supports the extension of the default theory. This is, in effect, what the theory of nonmonotonic sorts gives you. This...

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  • 1.2 Canonical Level This intermediate level of representation usually consists of the verb itself, (or perhaps a more primitive semantic predicate chosen to represent the verb) and a list of possible roles, e.g. arguments to the predicate. These roles correspond loosely to a union of the various semantic types indicated in the schemas. The schemas above could all easily map i n t o : SUPPORTS(l,2, ,).

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  • An improved version of IRACQ (for Interpretation Rule ACQuisition) is presented. I Our approach to semantic knowledge acquisition: 1 ) is in the context of a general purpose NL interface rather than one that accesses only databases, 2) employs a knowledge representation formalism with limited inferencing capabilities, 3) assumes a trained person but not an AI expert, and 4) provides a complete environment for not only acquiring semantic knowledge, but also maintaining and editing it in a consistent knowledge base. IRACQ is currently in use at the Naval Ocean Systems Center. ...

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  • Japanese has m a n y noun phrase patterns of the type A no B consisting of two nouns A and B with an adnominal particle no. As the semantic relations between the two nouns in the noun phrase are not made explicit, the interpretation of the phrases depends mainly on the semantic characteristics of the nouns. This paper describes the semantic diversity of A no B and a method of semantic analysis for such phrases based on feature unification.

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  • In this paper, we explore unsupervised techniques for the task of automatic short answer grading. We compare a number of knowledge-based and corpus-based measures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel technique to improve the performance of the system by integrating automatic feedback from the student answers. Overall, our system significantly and consistently outperforms other unsupervised methods for short answer grading that have been proposed in the past. ...

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  • The book reports on an attempt to understand the unity of physics. This unity began to manifest itself in rather unexpected form in this century. The most important step in that direction was the development of quantum theory; the emphasis of this book is therefore on the endeavor to understand quantum theory. Here, understand refers not merely to practical application of the theory—in that sense it has been understood for a long time. It means being able to say what one does when applying the theory....

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  • To solve the problems caused by the merger, no schema changes are required. Merge the customer entity sets removing duplicate tuples with the same social- security field. Before merging the branch entity sets, prepend the old bank name to the branch-name attributeineachtuple.The employee entity sets can bemerged directly, and so can the payment entity sets. No duplicate removal should be performed. Before merging the loan and account entity sets, whenever there is a number common in both the banks, the old number is replaced by a new unique number, in one of the banks....

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  • Possibilities can be explained from several semantic aspects. One way to explain possibility is ease of achievement. Another way is plausibility; that is, the propensity of an event to occur, which relates to the concept of “potential surprise”. A third way to explain possibility is logical consistency with available information. Finally, possibility can be explained as preference, referring to the willingness of an agent to make a decision. Possibility is dually related to necessity in the sense that “not A” being not possible means that A is necessary.

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  • A practical agent programming language discusses the need for an eective and practical bdi based agent oriented programming language. It proposes an alternative by presenting the syn tax and semantics of a programming language, called 2apl (a practical agent programming language). This programming language facilitates the implementation of multi agent systems consisting of individual cognitive agents.

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  • Data granularity: The data within a P2P system can be accessible at many degrees of granularity. At the atomic granularity level, data consists of a collection of indivisible objects, e.g., complete MP3 files. For data placement at this level, we have to either place an entire object at a peer, or not at all; this is the semantics currently supported by today’s P2P systems. At the hierarchical granularity level, sets of objects can be grouped into larger objects, thus forming hierarchies.

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  • GernEdiT (short for: GermaNet Editing Tool) offers a graphical interface for the lexicographers and developers of GermaNet to access and modify the underlying GermaNet resource. GermaNet is a lexical-semantic wordnet that is modeled after the Princeton WordNet for English. The traditional lexicographic development of GermaNet was error prone and time-consuming, mainly due to a complex underlying data format and no opportunity of automatic consistency checks.

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  • The internal structure of the locative predicate-complement form-class in German is described within the framework of a generative grammar consisting of a phrase-structure (PS) component, a semantic (S) component, and a transformation (T) component. The S-component is interposed between the PS-component and the T-component.

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  • Maintaining high annotation consistency in large corpora is crucial for statistical learning; however, such work is hard, especially for tasks containing semantic elements. This paper describes predicate argument structure analysis using transformation-based learning. An advantage of transformation-based learning is the readability of learned rules.

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