As machine translation technology improves comparisons to human performance are often made in quite general and exaggerated terms. Thus, it is important to be able to account for differences accurately. This paper reports a simple, descriptive scheme for comparing translations and applies it to two translations of a British opinion article published in March, 2017. One is a human translation (HT) into Swedish, and the other a machine translation (MT). While the comparison is limited to one text, the results are indicative of current limitations in MT.

As for any categorial scheme used for annotation, UD abound with borderline cases. The main instruments to resolve them are the UD design principles and, of course, the linguistic facts of the matter. UD makes a fundamental distinction between content words and function words, and a, perhaps less fundamental, distinction between pure function words and the rest. It has been suggested that adpositions are to be included among the pure function words. In this paper I discuss the case of prepositions in Swedish and related languages in the light of these distinctions. It relates to a more general problem: How should we resolve cases where the linguistic intuitions and UD design principles are in conflict?

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Science education research suggests that our everyday intuitions of motion and interaction of physical objects fit well with how physicists use the term “momentum”. Corpus linguistics provides an easily accessible approach to study language in different domains, including everyday language. Analysis of language samples from English text corpora reveals a trend of increasing metaphorical use of “momentum” in non-science domains, and through conceptual metaphor analysis, we show that the use of the word in everyday language, as opposed to for instance “force”, is largely adequate from a physics point of view. In addition, “momentum” has recently been borrowed into Swedish as a metaphor in domains such as sports, politics and finance, with meanings similar to those in physics. As an implication for educational practice, we find support for the suggestion to introduce the term “momentum” to English-speaking pupils at an earlier age than what is typically done in the educational system today, thereby capitalising on their intuitions and experiences of everyday language. For Swedish-speaking pupils, and possibly also relevant to other languages, the parallel between “momentum” and the corresponding physics term in the students’ mother tongue could be made explicit.

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In principle the CLARIN research infrastructure provides a good environment to support research on translation. In reality, the progress within CLARIN in this area seems to be fairly slow. In this paper I will give examples of the resources currently available, and suggest what is needed to achieve a relevant research infrastructure for translation studies. Also, I argue that translation studies has more to gain from language technology, and statistical machine translation in particular, than what is generally assumed, and give some examples.

The paper offers an effective way of teacher-student computer-based collabo-ration in translation class. We show how a quantitative-qualitative method of analysis supported by word alignment technology can be applied to student translations for use in the classroom. The combined use of natural-language pro-cessing and manual techniques enables students to ‘co-emerge’ during highly motivated collaborative sessions. Within the advocated approach, students are pro-active seekers for a better translation (grade) in a teacher-centered computer-based peer-assisted translation class.

Using the technique of semantic mirroring a graph is obtained that represents words and their translationsfrom a parallel corpus or a bilingual lexicon. The connectedness of the graph holds information about the semanticrelations of words that occur in the translations. Spectral graph theory is used to partition the graph, which leadsto a grouping of the words in different clusters. We illustrate the method using a small sample of seed words froma lexicon of Swedish and English adjectives and discuss its application to computational lexical semantics andlexicography.