نتایج جستجو برای: syntactic dependency parsing
تعداد نتایج: 79646 فیلتر نتایج به سال:
The paper presents a method of automatic enrichment of a very large dictionary of word combinations. The method is based on results of automatic syntactic analysis (parsing) of sentences. The dependency formalism is used for representation of syntactic trees that allows for easier treatment of information about syntactic compatibility. Evaluation of the method is presented for the Spanish langu...
We present a study on the dependency parsing of second language learner data, focusing less on the parsing techniques and more on the effect of the linguistic distinctions made in the data. In particular, we examine syntactic annotation that relies more on morphological form than on meaning. We see the effect of particular linguistic decisions by: 1) converting and transforming a training corpu...
We present a study on two key characteristics of human syntactic annotations: anchoring and agreement. Anchoring is a well known cognitive bias in human decision making, where judgments are drawn towards preexisting values. We study the influence of anchoring on a standard approach to creation of syntactic resources where syntactic annotations are obtained via human editing of tagger and parser...
Existing semantic parsing research has steadily improved accuracy on a few domains and their corresponding meaning representations. In this paper, we present a novel supervised semantic parsing algorithm, which includes the lexicon extension and the syntactic supervision. This algorithm adopts a large-scale knowledge base from the open-domain Freebase to construct efficient, rich Combinatory Ca...
We describe a system for semantic role labeling adapted to a dependency parsing framework. Verb arguments are predicted over nodes in a dependency parse tree instead of nodes in a phrase-structure parse tree. Our system participated in SemEval-2015 shared Task 15, Subtask 1: CPA parsing and achieved an Fscore of 0.516. We adapted features from prior semantic role labeling work to the dependency...
We develop novel firstand second-order features for dependency parsing based on the Google Syntactic Ngrams corpus, a collection of subtree counts of parsed sentences from scanned books. We also extend previous work on surface n-gram features from Web1T to the Google Books corpus and from first-order to second-order, comparing and analysing performance over newswire and web treebanks. Surface a...
We present a study on two key characteristics of human syntactic annotations: anchoring and agreement. Anchoring is a well known cognitive bias in human decision making, where judgments are drawn towards preexisting values. We study the influence of anchoring on a standard approach to creation of syntactic resources where syntactic annotations are obtained via human editing of tagger and parser...
Research in syntactic parsing is largely driven by progress in intrinsic evaluation and there have been impressive developments in recent years in terms of evaluation measures, such as F-score or labeled accuracy. At the same time, a range of different syntactic representations have been put to use in treebank annotation projects and there have been studies measuring various aspects of the ”lea...
Graph-based dependency parsing algorithms commonly employ features up to third order in an attempt to capture richer syntactic relations. However, each level and each feature combination must be defined manually. Besides that, input features are usually represented as huge, sparse binary vectors, offering limited generalization. In this work, we present a deep architecture for dependency parsin...
In many languages general syntactic cues are insufficient to disambiguate crucial relations in the task of Parsing. In such cases semantics is necessary. In this paper we show the effect of minimal semantics on parsing. We did experiments on Hindi, a morphologically rich free word order language to show this effect. We conducted experiments with the two data-driven parsers MSTPaser and MaltPars...
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