method ID: ccgparser

Related Papers

Object-Extraction and Question-Parsing using CCG

Authors: nan

Publication: TIPSTER (2004)

DOI: nan

Accurate dependency recovery has recently been reported for a number of wide-coverage statistical parsers using Combinatory Categorial Grammar (CCG). However, overall figures give no indication of a parser’s performance on …...

44970

The Importance of Supertagging for Wide-Coverage CCG Parsing

Authors: nan

Publication: TIPSTER (2004)

DOI: nan

This paper describes the role of supertagging in a wide-coverage CCG parser which uses a log-linear model to select an analysis. The supertagger reduces the derivation space over which model …...

6098

Formalism-Independent Parser Evaluation with CCG and DepBank

Authors: nan

Publication: TIPSTER (2007)

DOI: nan

A key question facing the parsing commu- nity is how to compare parsers which use different grammar formalisms and produce different output. Evaluating a parser on the same resource used …...

36048

Adapting a Lexicalized-Grammar Parser to Contrasting Domains

Authors: nan

Publication: TIPSTER (2008)

DOI: nan

Most state-of-the-art wide-coverage parsers are trained on newspaper text and suffer a loss of accuracy in other domains, making parser adaptation a pressing issue. In this paper we demonstrate that …...

44874

Faster Parsing by Supertagger Adaptation

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

We propose a novel self-training method for a parser which uses a lexicalised gram- mar and supertagger, focusing on increas- ing the speed of the parser rather than its accuracy. …...

36177

Linguistic Steganography Using Automatically Generated Paraphrases

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

This paper describes a method for checking the acceptability of paraphrases in context. We use the Google n-gram data and a CCG parser to certify the paraphrasing grammati- cality and …...

23788

SCHWA: PETE Using CCG Dependencies with the C&C Parser

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

This paper describes the SCHWA system entered by the University of Sydney in Se- mEval 2010 Task 12 – Parser Evaluation using Textual Entailments (Yuret et al., 2010). Our system …...

22948

A Comparison of Loopy Belief Propagation and Dual Decomposition for Integrated CCG Supertagging and Parsing

Authors: nan

Publication: TIPSTER (2011)

DOI: nan

Via an oracle experiment, we show that the upper bound on accuracy of a CCG parser is significantly lowered when its search space is pruned using a supertagger, though the …...

36381

Training a Log-Linear Parser with Loss Functions via Softmax-Margin

Authors: nan

Publication: TIPSTER (2011)

DOI: nan

Log-linear parsing models are often trained by optimizing likelihood, but we would prefer to optimise for a task-specific metric like F- measure. Softmax-margin is a convex objec- tive for such …...

44388

Improved CCG Parsing with Semi-supervised Supertagging

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

AbstractCurrent supervised parsers are limited by the size of their labelled training data, making improving them with unlabelled data an important goal. We show how a state-of-the-art CCG parser can …...

19860

Higher-order logical inference with compositional semantics

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

We present a higher-order inference sys- tem based on a formal compositional semantics and the wide-coverage CCG parser. We develop an improved method to bridge between the parser and seman- …...

34345

Human-in-the-Loop Parsing

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

This paper demonstrates that it is possible for a parser to improve its performance with a hu- man in the loop, by posing simple questions to non-experts. For example, given …...

33468

Max-Margin Incremental CCG Parsing

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractIncremental syntactic parsing has been an active research area both for cognitive scientists trying to model human sentence processing and for NLP researchers attempting to combine incremental parsing with language …...

37678