Tjong Kim Sang (2000) describes how a systeminternal combination of memory-based learners can be used for base noun phrase (baseNP) recognition. The idea is to generate different chunking models by using different chunk representations. Chunks can be represented with bracket structures but alternatively one can use a tagging representation which classifies words as being inside a chunk (I), out...

this paper presents an attempt to analyze the verb phrase ellipsis in persian in terms of the questions of identity and licensing. assuming a minimalist framework for the analysis, it is argued that verb phrase ellipsis in persian is structurally licensed by a governing head which takes vp as its complement, through an algorithm of e(llipsis)-feature deletion at pf. it is also shown that struct...

This research presents an approach for an English-to-Arabic Machine Translation System based on Building correct grammar and phrase structures first and then automatically deriving Translation Rules for phrase translation. For every English phrase, the grammar is first analysed and then a corresponding Arabic translation is given which would be used by the machine learning system to produce a t...

We compare three approaches to statistical machine translation (pure phrase-based, factored phrase-based and neural) by performing a fine-grained manual evaluation via error annotation of the systems’ outputs. The error types in our annotation are compliant with the multidimensional quality metrics (MQM), and the annotation is performed by two annotators. Inter-annotator agreement is high for s...

Case-based reasoning is a promising approach to develop a tutoring system. However, there still remains some problems to be solved. First, the system should explain the inference procedure upon the user’s requests. Second, the explanation structure in the case may be inconsistent during the adaptation process. Third, when the system finds a gap between the new problem situation and the retrieve...

Transfer-based Machine Translation systems require a procedure for choosing the set of transfer rules for generating a target language translation from a given source language sentence. In an MT system with many competing transfer rules, choosing the best set of transfer rules for translation may involve the evaluation of an explosive number of competing sets. We propose a solution to this prob...

Statistical phrase-based machine translation systems make only little use of context information: while the language model takes into account target side context, context information on the source side is typically not integrated into phrase-based translation systems. Translational features such as phrase translation probabilities are learned from phrase-translation pairs extracted from word-al...

This work describes an experimental evaluation of the significance of phrasal verb treatment for obtaining better quality statistical machine translation (SMT) results. Phrasal verbs are multiword expressions used frequently in English, independent of the domain and degree of formality of language. They are challenging for natural language processing due to their idiosyncratic semantic and synt...

Although more additional corpora are now available for Statistical Machine Translation (SMT), only the ones which belong to the same or similar domains with the original corpus can indeed enhance SMT performance directly. Most of the existing adaptation methods focus on sentence selection. In comparison, phrase is a smaller and more fine grained unit for data selection, therefore we propose a s...

Structured syntactic knowledge is important for phrase reordering. This paper proposes using convolution tree kernel over source parse tree to model structured syntactic knowledge for BTG-based phrase reordering in the context of statistical machine translation. Our study reveals that the structured syntactic features over the source phrases are very effective for BTG constraint-based phrase re...