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The UCREL team at the University of Lancaster is engaged in the development of a robust parsing mechanism, which will assign the appro- priate grammatical structure to sentences in unconstrained …...

Research in example-based machine translation (F,I~MT) has been hampered by the lack of efficient tree alignment al- gorithms for bilingual corpora. *ghis pa- per <lescribes an alignment algorithm for F,I~MT …...

We present a connectionist architecture and demon- strate that it can learn syntactic parsing from a cor- pus of parsed text. The architecture can represent syntactic constituents, and can learn …...

We present Minimum Bayes-Risk word alignment for machine translation. This statistical, model-based approach attempts to minimize the expected risk of align- ment errors under loss functions that mea- sure alignment …...

We present Minimum Bayes-Risk (MBR) de- coding for statistical machine translation. This statistical approach aims to minimize expected loss of translation errors under loss functions that measure translation performance. We …...

Previous research applying kernel meth- ods to natural language parsing have fo- cussed on proposing kernels over parse trees, which are hand-crafted based on do- main knowledge and computational con- …...

This paper proposes to use a convolution kernel over parse trees to model syntactic structure information for relation extrac- tion. Our study reveals that the syntactic structure features embedded in …...

Syntactic Features for Text Categorisation Ari Chanen School of Information Technologies University of Sydney Sydney, Australia, 2006 ari@it.usyd.edu.au Jon Patrick School of Information Technologies University of Sydney Sydney, Australia, 2006 …...

We present an algorithm for unsupervised induction of labeled parse trees. The al- gorithm has three stages: bracketing, ini- tial labeling, and label clustering. Brack- eting is done from raw …...

We investigate the usefulness of syntactic knowledge in estimating the quality of English-French translations. We find that dependency and constituency tree kernels perform well but the error rate can be …...

AbstractIncorporating syntactic information in Neural Machine Translation (NMT) can lead to better reorderings, particularly useful when the language pairs are syntactically highly divergent or when the training bitext is not …...

Code generation is the task of generating code snippets from input user specifications in nat- ural language. Leveraging the linguistically- motivated hierarchical structure of the input can benefit code generation, …...

AbstractRecent advancements in pre-trained language models (PLMs) have demonstrated that these models possess some degree of syntactic awareness. To leverage this knowledge, we propose a novel chart-based method for extracting …...