D3. 8 Lexical-semantic analytics for NLP

The present document illustrates the work carried out in task 3.3 (work package 3) focused on lexicalsemantic analytics for Natural Language Processing (NLP). This task aims at computing analytics for lexicalsemantic information such as words, senses and domains in the available resources, investigating their role in NLP applications. Specifically, this task concentrates on three research directions, namely i) which grouping senses based on their semantic similari sense clustering , in ty improves the performance of NLP tasks such as Word Sense Disambiguation (WSD), ii) domain labeling of text , in which the lexicographic resources made available by the ELEXIS project for research purposes allow better performances to be achieved, and fin senses ally iii) analysing the , for which a software package is made available. diachronic distribution of In this deliverable, we illustrate the research activities aimed at achieving the aforementioned goals and put forward suggestions for future works. Importantly, we stress the crucial role played by highquality lexicalsemantic r esources when investigating such linguistic aspects and their impact on NLP applications. To this end, as an additional contribution, we address the paucity of manually the ELEXIS parallelannotated data in the lexical senseannotated datasetsemantic research field and introduce , a novel entirely manuallyavailable in 10 European languages and featuring 5 annotation layers.