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Temporal and numerical expression understanding is of great importance inmany downstream Natural Language Processing (NLP) and Information Retrieval(IR) tasks. However, much previous work covers only a few sub-types and focusesonly on entity extraction, which severely limits the usability of identifiedmentions. In order for such entities to be useful in downstream scenarios,coverage and granularity of sub-types are important; and, even more so,providing resolution into concrete values that can be manipulated. Furthermore,most previous work addresses only a handful of languages. Here we describe amulti-lingual evaluation dataset - NTX - covering diverse temporal andnumerical expressions across 14 languages and covering extraction,normalization, and resolution. Along with the dataset we provide a robustrule-based system as a strong baseline for comparisons against other models tobe evaluated in this dataset. Data and code are available at\url{https://aka.ms/NTX}.

Dataset and Baseline System for Multi-lingual Extraction and Normalization of Temporal and Numerical Expressions