A Crossing-Sensitive Third-Order Factorization for Dependency Parsing
نویسنده
چکیده
Parsers that parametrize over wider scopes are generally more accurate than edge-factored models. For graph-based non-projective parsers, wider factorizations have so far implied large increases in the computational complexity of the parsing problem. This paper introduces a “crossing-sensitive” generalization of a third-order factorization that trades off complexity in the model structure (i.e., scoring with features over multiple edges) with complexity in the output structure (i.e., producing crossing edges). Under this model, the optimal 1-Endpoint-Crossing tree can be found in O(n) time, matching the asymptotic run-time of both the third-order projective parser and the edge-factored 1-EndpointCrossing parser. The crossing-sensitive thirdorder parser is significantly more accurate than the third-order projective parser under many experimental settings and significantly less accurate on none.
منابع مشابه
Models for Improved Tractability and Accuracy in Dependency Parsing
MODELS FOR IMPROVED TRACTABILITY AND ACCURACY IN DEPENDENCY PARSING Emily Pitler Mitchell P. Marcus Sampath Kannan Automatic syntactic analysis of natural language is one of the fundamental problems in natural language processing. Dependency parses (directed trees in which edges represent the syntactic relationships between the words in a sentence) have been found to be particularly useful for ...
متن کاملتأثیر ساختواژهها در تجزیه وابستگی زبان فارسی
Data-driven systems can be adapted to different languages and domains easily. Using this trend in dependency parsing was lead to introduce data-driven approaches. Existence of appreciate corpora that contain sentences and theirs associated dependency trees are the only pre-requirement in data-driven approaches. Despite obtaining high accurate results for dependency parsing task in English langu...
متن کاملAn improved joint model: POS tagging and dependency parsing
Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do the POS tagging task along with dependency parsing in a pipeline mode. Unfortunately, in pipel...
متن کاملGraph-based Dependency Parsing with Bidirectional LSTM
In this paper, we propose a neural network model for graph-based dependency parsing which utilizes Bidirectional LSTM (BLSTM) to capture richer contextual information instead of using high-order factorization, and enable our model to use much fewer features than previous work. In addition, we propose an effective way to learn sentence segment embedding on sentence-level based on an extra forwar...
متن کاملA subtree-based factorization of dependency parsing
We propose a dependency parsing pipeline, in which the parsing of long-distance projections and localized dependencies are explicitly decomposed at the input level. A chosen baseline dependency parsing model performs only on ’carved’ sequences at the second stage, which are transformed from coarse constituent parsing outputs at the first stage. When k-best constituent parsing outputs are kept, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- TACL
دوره 2 شماره
صفحات -
تاریخ انتشار 2014