We provide a summary of the sixth edition of the CASE workshop that is held in the scope of
RANLP 2023. The workshop consists of regular papers, three keynotes, working papers of …

The ability to generalise well is one of the primary desiderata of natural language
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …

Benchmarking state-of-the-art text classification and information extraction systems in
multilingual, cross-lingual, few-shot, and zero-shot settings for socio-political event …

Supervised models can achieve very high accuracy for fine-grained text classification. In
practice, however, training data may be abundant for some types but scarce or even non …

There is a large and growing body of literature on datasets created to facilitate the study of
socio-political events of conflict and unrest. However, the datasets, and the approaches …

The recent advances in transfer learning techniques and pre-training of large contextualized
encoders foster innovation in real-life applications, including dialog assistants. Practical …

Is it possible accurately classify political relations within evolving event ontologies without
extensive annotations? This study investigates zero-shot learning methods that use expert …

Recent supervised models for event coding vastly outperform pattern-matching methods.
However, their reliance solely on new annotations disregards the vast knowledge within …

This paper describes a new corpus consisting of circa 4.5 K news snippets (multi-) labelled
with finegrained infectious disease-related event types. The paper presents the underlying …

We report on the current status of an effort to produce political event data from unstructured
text via a Transformer language model. Compelled by the current lack of publicly available …