Idioms pose unique challenges for machine translation due to their metaphorical nature and cultural nuances. Consequently, they often present a translation problem even for humans. This longitudinal study evaluates the performance of ChatGPT in translating idiomatic expressions between English and Croatian, comparing results across two time points. The test set comprises 72 idioms in each translation direction, divided into three categories based on equivalence: complete, partial, and zero, with each category representing one-third of the set. The evaluation considers three layers: translation of the isolated idiom, translation of an online excerpt containing the idiom, and translation of a self-constructed example sentence. As expected, accuracy generally declined with decreasing equivalence. However, a follow-up study conducted six months later highlighted the need for continuous monitoring of machine translation tools.

This paper aims at identifying a specific set of collocations known under the term metaphorical collocations. In this type of collocations, a semantic shift has taken place in one of the components. Since the appropriate gold standard needs to be compiled prior to any serious endeavour to extract metaphorical collocations automatically, this paper first presents the steps taken to compile it, and then establishes appropriate evaluation framework. The process of compiling the gold standard is illustrated on one of the most frequent Croatian nouns, which resulted in the preliminary relation significance set. With the aim to investigate the possibility of facilitating the process, frequency, logDice, relation, and pretrained word embeddings are used as features in the classification task conducted on the logDice-based word sketch relation lists. Preliminary results are presented.

Parallel corpora constitute a unique re-source for providing assistance to human translators. The selection and preparation of the parallel corpora also conditions the quality of the resulting MT engine. Since Croatian is a national language and Italian is officially recognized as a minority lan-guage in seven cities and twelve munici-palities of Istria County, a large amount of parallel texts is produced on a daily basis. However, there have been no attempts in using these texts for compiling a parallel corpus. A domain-specific sentence-aligned parallel Croatian-Italian corpus of administrative texts would be of high value in creating different language tools and resources. The aim of this paper is, therefore, to explore the value of parallel documents which are publicly available mostly in pdf format and to investigate the use of automatically-built dictionaries in corpus compilation. The effects that a document format and, consequently sentence splitting, and the dictionary input have on the sentence alignment process are manually evaluated.