The paper introduces [DATASET], a resource that builds on the ValPaL database of verbs’ valency patterns and alternations by adding a number of ancient languages (completely absent from ValPaL) and a number of new features that enable direct comparison, both diachronic and synchronic. For each verb, ValPaL contains the basic frame and ideally all possible valency alternations allowed by the verb (e.g. passive, causative, reflexive etc.). In order to enable comparison among alternations, an additional level has been added, the alternation class, that overcomes the issue of comparing language specific alternations which were added by individual contributors of ValPaL. The ValPaL had as its main aim typological comparison, and data collection was variously carried out using questionnaires, secondary sources and largely drawing on native speakers’ intuition by contributors. Working with ancient languages entails a methodological change, as the data is extracted from corpora. This has led to re-thinking the notion of valency as a usage-based feature of verbs and to planning future addition of corpus data to modern languages in the database. It further shows the impact of ancient languages on theoretical reflection.

This paper addresses challenges encountered in constructing lexical databases, specifically WordNets, for three ancient Indo-European languages: Ancient Greek, Latin, and Sanskrit. The difficulties partly arise from adapting concepts and methodologies designed for modern languages to the construction of lexical resources for ancient ones. A further significant challenge arises from the goal of creating WordNets that not only adhere to a neo-structuralist relational view of meaning but also integrate Cognitive Semantics concepts, aiming for a more realistic representation of meaning. This integration is crucial for facilitating studies in diachronic semantics and lexicology, and representing meaning in such a nuanced manner becomes paramount when constructing language resources for theoretical research, rather than for applied tasks, as is the case with lexical resources for ancient languages. The paper delves into these challenges through a case study focused on the TEMPERATURE conceptual domain in the three languages. It outlines difficulties in distinguishing prototypical and non-prototypical senses, literal and non-literal ones, and, within non-literal meanings, between metaphorical and metonymic ones. Solutions adopted to address these challenges are presented, highlighting the necessity of achieving maximum granularity in meaning representation while maintaining a sustainable workflow for annotators.