搜索结果: 1-15 共查到“应用语言学 dependency”相关记录18条 . 查询时间(0.031 秒)
Transition-Based Parsing for Deep Dependency Structures
Analysis of structure depth dependency structure language data drive
2016/10/31
Derivations under different grammar formalisms allow extraction of various dependency structures. Particularly, bilexical deep dependency structures beyond surface tree representation can be derived f...
Integrating Selectional Constraints and Subcategorization Frames in a Dependency Parser
Integrating Selectional Constraints Subcategorization Frames Dependency Parser
2016/4/7
Statistical parsers are trained on treebanks that are composed of a few thousand sentences. In order to prevent data sparseness and computational complexity, such parsers make strong independence hypo...
Phrase Dependency Machine Translation with Quasi-Synchronous Tree-to-Tree Features
phrase translation
2015/9/14
Recent research has shown clear improvement in translation quality by exploiting linguistic
syntax for either the source or target language. However, when using syntax for both languages
(“tree-to-t...
Divisible Transition Systems and Multiplanar Dependency Parsing
Divisible Transition Systems Multiplanar Dependency Parsing
2015/9/11
Transition-based parsing is a widely used approach for dependency parsing that combines high efficiency with expressive feature models. Many different transition systems have been proposed, often form...
Dependency Parsing Schemata and Mildly Non-Projective Dependency Parsing
Dependency Parsing Schemata Mildly Non-Projective Dependency Parsing
2015/9/9
We introduce dependency parsing schemata, a formal framework based on Sikkel's parsing schemata for constituency parsers, which can be used to describe, analyze, and compare dependency parsing algorit...
String-to-Dependency Statistical Machine Translation
String-to-Dependency Statistical Machine Translation
2015/9/8
We propose a novel string-to-dependency algorithm for statistical machine translation. This algorithm employs a target dependency language model during decoding to exploit long distance word relations...
Wide-Coverage Deep Statistical Parsing Using Automatic Dependency Structure Annotation
Wide-Coverage Deep Statistical Parsing Automatic Dependency Structure Annotation
2015/9/6
A number of researchers have recently conducted experiments comparing “deep” hand-crafted wide-coverage with “shallow” treebank- and machine-learning-based parsers at the level of dependencies, using ...
Algorithms for Deterministic Incremental Dependency Parsing
Dependency Parsing Computing language
2015/9/6
Parsing algorithms that process the input from left to right and construct a single derivation
have often been considered inadequate for natural language parsing because of the massive
ambiguity typ...
Multi-labeled corpora, where each document is tagged with a set of labels, are ubiquitous. When the number of unique labels in the dataset is large, there are naturally some dependencies among the lab...
CCGbank: A Corpus of CCG Derivations and Dependency Structures Extracted from the Penn Treebank
Dependency Structures Extracted CCG Derivations
2015/9/2
This article presents an algorithm for translating the Penn Treebank into a corpus of Combinatory Categorial Grammar (CCG) derivations augmented with local and long-range word–word
dependencies. The ...
Traditionally, vector-based semantic space models use word co-occurrence counts from large
corpora to represent lexical meaning. In this article we present a novel framework for constructing semantic...
Dependency Parsing with an Extended Finite-State Approach
Extended Finite-State Approach Dependency Parsing
2015/8/28
This article presents a dependency parsing scheme using an extended finite-state approach. The
parser augments input representation with “channels” so that links representing syntactic dependen...
Learning Dependency Translation Models as Collections of Finite-State Head Transducers
Translation Models Finite-State Head Transducers
2015/8/25
The paper defines weighted head transducers, finite-state machines that perform middle-out string
transduction. These transducers are strictly more expressive than the special case of sta...
Learning Random Walk Models for Inducing Word Dependency Distributions
Random Walk Models Inducing Word Dependency
2015/6/12
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the sparseness of counts...
Deep dependencies from context-free statistical parsers:correcting the surface dependency approximation
Deep dependencies statistical parsers surface dependency approximation
2015/6/12
We present a linguistically-motivated algorithm for reconstructing nonlocal dependency in broad-coverage context-free parse trees derived from treebanks. We use an algorithm based on loglinear classif...
