Тәуелділік құрылымдары

Proof-Nets (Roorda 1990) are a good device for processing with eategorial grammars, mainly because they avoid spurious ambiguities. Nevertheless, they do not provide easily readable structures and they hide the …...

\Ve are proposing a new framework of statisti- cal language modeling which integrates lexical .association statistics with syntactic preference, while maintaining the modularity of those differ- ent statistics types, facilitating …...

This paper describes a wide-coverage sta- tistical parser that uses Combinatory Cat- egorial Grammar (CCG) to derive de- pendency structures. The parser differs from most existing wide-coverage tree- bank parsers …...

We describe a method for enriching the output of a parser with information available in a corpus. The method is based on graph rewriting using memory- based learning, applied to …...

Previous models in syntax-based statistical machine translation usually resort to some kinds of synchronous procedures, few of these works are based on the analysis-transfer-generation methodology. In this paper, we present …...

We present a multi-view annotation framework for Chinese treebanking, which uses dependen- cy structures as the base view and supports conversion into phrase structures with minimal loss of information. A …...

AbstractThe role of language models in SMT is to promote fluent translation output, but traditional n-gram language models are unable to capture fluency phenomena between distant words, such as some …...

In this paper, we propose three different methods for automatic evaluation of the machine translation (MT) quality. Two of the metrics are trainable on direct- assessment scores and two of …...

AbstractEvent extraction for the biomedical domain is more challenging than that in the general news domain since it requires broader acquisition of domain-specific knowledge and deeper understanding of complex contexts. …...

AbstractAbstract Meaning Representations (AMRs) capture sentence-level semantics structural representations to broad-coverage natural sentences. We investigate parsing AMR with explicit dependency structures and interpretable latent structures. We generate the latent soft …...

AbstractBy introducing a small set of additional parameters, a probe learns to solve specific linguistic tasks (e.g., dependency parsing) in a supervised manner using feature representations (e.g., contextualized embeddings). The …...

AbstractRecent work has identified properties of pretrained self-attention models that mirror those of dependency parse structures. In particular, some self-attention heads correspond well to individual dependency types. Inspired by these …...