The recognition of Tibetan interrogative sentences is a basic work in natural language processing, which has wide application value terms syntactic analysis, semantic intelligent question answering, search engine and other research fields. Employing pronouns as entry point to analyze the phrase features before after pronouns, paper proposes method for sentence classification based on by designi...

This paper deals with the underspeciied semantic representation of ellipsis and its resolution. We present an analysis to explain the distribution of strict and sloppy readings in the interaction of verb phrase ellipsis and anaphora. The analysis is integrated into a framework that enables a uniform and underspeciied treatment of scope, anaphora and VPE.

In this paper, we describe a novel phrase reordering model based on predicate-argument structure. Our phrase reordering method utilizes a general predicate-argument structure analyzer to reorder source language chunks based on predicate-argument structure. We explicitly model longdistance phrase alignments by reordering arguments and predicates. The reordering approach is applied as a preproces...

This paper describes the phrase-based SMT systems developed for our participation in the WMT11 Shared Translation Task. Translations for English↔German and English↔French were generated using a phrase-based translation system which is extended by additional models such as bilingual and fine-grained POS language models, POS-based reordering, lattice phrase extraction and discriminative word alig...

We present two translation systems experimented for the shared-task of “Workshop on Statistical Machine Translation,” a phrase-based model and a hierarchical phrase-based model. The former uses a phrasal unit for translation, whereas the latter is conceptualized as a synchronousCFG in which phrases are hierarchically combined using non-terminals. Experiments showed that the hierarchical phraseb...

This paper investigates the application of vector space models (VSMs) to the standard phrase-based machine translation pipeline. VSMs are models based on continuous word representations embedded in a vector space. We exploit word vectors to augment the phrase table with new inferred phrase pairs. This helps reduce out-of-vocabulary (OOV) words. In addition, we present a simple way to learn bili...

In this paper, we present a novel distortion model for phrase-based statistical machine translation. Unlike the previous phrase distortion models whose role is to simply penalize nonmonotonic alignments[1, 2], the new model assigns the probability of relative position between two source language phrases aligned to the two adjacent target language phrases. The phrase translation probabilities an...