Cross-Level Semantic Similarity in Newswire Texts and Software Code Comments: Insights from Serbian Data in the AVANTES Project

This paper presents the Serbian datasets developed within the project Advancing Novel Textual Similarity-based Solutions in Software Development – AVANTES, intended for the study of Cross-Level Semantic Similarity (CLSS). CLSS measures the level of semantic overlap between texts of different lengths, and it also refers to the problem of establishing such a measure automatically. The problem was first formulated about a decade ago, but research on it has been sparse and limited to English. The AVANTES project aims to change this through the study of CLSS in Serbian, focusing on two different text domains – newswire and software code comments – and on two text length combinations – phrase-sentence and sentence-paragraph. We present and compare two newly created datasets, describing the process of their annotation with fine-grained semantic similarity scores, and outlining a preliminary linguistic analysis. We also give an overview of the ongoing detailed linguistic annotation targeted at detecting the core linguistic indicators of CLSS.