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Deep syntactic processing

Xem 1-7 trên 7 kết quả Deep syntactic processing
  • We present a novel approach for finding discontinuities that outperforms previously published results on this task. Rather than using a deeper grammar formalism, our system combines a simple unlexicalized PCFG parser with a shallow pre-processor. This pre-processor, which we call a trace tagger, does surprisingly well on detecting where discontinuities can occur without using phase structure information.

    pdf8p bunbo_1 17-04-2013 19 1   Download

  • We present a model for sentence compression that uses a discriminative largemargin learning framework coupled with a novel feature set defined on compressed bigrams as well as deep syntactic representations provided by auxiliary dependency and phrase-structure parsers. The parsers are trained out-of-domain and contain a significant amount of noise. We argue that the discriminative nature of the learning algorithm allows the model to learn weights relative to any noise in the feature set to optimize compression accuracy directly.

    pdf8p bunthai_1 06-05-2013 28 1   Download

  • To investigate the contributions of taggers or chunkers to the performance of a deep syntactic parser, Weighted Constraint Dependency Grammars have been extended to also take into consideration information from external sources. Using a weak information fusion scheme based on constraint optimization techniques, a parsing accuracy has been achieved which is comparable to other (stochastic) parsers.

    pdf8p bunthai_1 06-05-2013 30 0   Download

  • In this paper, we focus on the features of a lexicon for Japanese syntactic analysis in Japanese-to-English translation. Japanese word order is almost unrestricted and Kc~uio-~ti (postpositional case particle) i s an i m p o r t a n t device which acts as the case label(case m a r k e r ) in Japanese sentences. Therefore case grammar is the most effective grammar for Japanese syntactic analysis. The case frame governed by )buc~n and having surface case(Kakuio-shi), deep case(case label) and semantic markers for nouns is analyzed here to illustrate how we apply case grammar to...

    pdf6p bungio_1 03-05-2013 30 2   Download

  • In recent years, machine learning (ML) has been used more and more to solve complex tasks in different disciplines, ranging from Data Mining to Information Retrieval or Natural Language Processing (NLP). These tasks often require the processing of structured input, e.g., the ability to extract salient features from syntactic/semantic structures is critical to many NLP systems. Mapping such structured data into explicit feature vectors for ML algorithms requires large expertise, intuition and deep knowledge about the target linguistic phenomena.

    pdf1p nghetay_1 07-04-2013 16 1   Download

  • We describe a novel method for coping with ungrammatical input based on the use of chart-like data structures, which permit anytime processing. Priority is given to deep syntactic analysis. Should this fail, the best partial analyses are selected, according to a shortest-paths algorithm, and assembled in a robust processing phase. The m e t h o d has been applied in a speech translation project with large HPSG grammars.

    pdf8p bunrieu_1 18-04-2013 30 3   Download

  • Entity relation detection is a form of information extraction that finds predefined relations between pairs of entities in text. This paper describes a relation detection approach that combines clues from different levels of syntactic processing using kernel methods. Information from three different levels of processing is considered: tokenization, sentence parsing and deep dependency analysis. Each source of information is represented by kernel functions.

    pdf8p bunbo_1 17-04-2013 19 1   Download

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