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We present the results of an experiment on extending the automatic method of Machine Translation evaluation BLUE with statistical weights for lexical items, such as tf.idf scores. We show that this extension gives additional information about evaluated texts; in particular it allows us to measure translation Adequacy, which, for statistical MT systems, is(More)
The extraction of dictionaries from parallel text corpora is an established technique. However, as parallel corpora are a scarce resource, in recent years the extraction of dictionaries using comparable corpora has obtained increasing attention. In order to find a mapping between languages, almost all approaches suggested in the literature rely on a seed(More)
We report on the results of an experiment aimed at enabling a machine translation system to select the appropriate strategy for dealing with words and phrases which have different translations depending on whether they are used as proper names or common nouns in the source text. We used the ANNIE named entity recognition system to identify named entities in(More)
Named entities create serious problems for state-of-the-art commercial machine translation (MT) systems and often cause translation failures beyond the local context, affecting both the overall morphosyntactic well-formedness of sentences and word sense disambiguation in the source text. We report on the results of an experiment in which MT input was(More)
In this paper we present and evaluate three approaches to measure comparability of documents in non-parallel corpora. We develop a task-oriented definition of comparability , based on the performance of automatic extraction of translation equivalents from the documents aligned by the proposed metrics, which formalises intuitive definitions of comparability(More)
In this paper we compare two methods for translating into English from languages for which few MT resources have been developed (e.g. Ukrainian). The first method involves direct transfer using an MT system that is available for this language pair. The second method involves translation via a cognate language, which has more translation resources and one or(More)
Lack of sufficient parallel data for many languages and domains is currently one of the major obstacles to further advancement of automated translation. The ACCURAT project is addressing this issue by researching methods how to improve machine translation systems by using comparable corpora. In this paper we present tools and techniques developed in the(More)
In this paper we present a tool that uses comparable corpora to find appropriate translation equivalents for expressions that are considered by translators as difficult. For a phrase in the source language the tool identifies a range of possible expressions used in similar contexts in target language corpora and presents them to the translator as a list of(More)
The output of state-of-the-art machine translation (MT) systems could be useful for certain NLP tasks, such as Information Extraction (IE). However, some unresolved problems in MT technology could seriously limit the usability of such systems. For example robust and accurate word sense disambiguation, which is essential for the performance of IE systems, is(More)