Argument mining (also known as “argumentation mining”) is a well-established research area in computational linguistics that focuses on the automatic identification of argumentative structures, such as premises, conclusions, and inference schemes. Since its beginnings, the focus has been on the development of large-scale argumentation dataset and tasks like argument quality assessment, argument persuasiveness, and the synthesis of argumentative texts, spanning various domains, such as legal, social, medical, political, and scientific settings.
The ASAIL workshop series and interest group serves as a platform for researchers and practitioners working on natural language processing of legal text. Its goals include (i) Organising regular peer-reviewed workshop events for presentation and discussion of research and practical implementations around legal NLP; (ii) Facilitating communication and collaboration among academic researchers as well as practitioners from industry, government, and the public sector, and other interested individuals and organisations; (iii) Providing an entry point into the research field and community.
The spirit of the conference is inclusive. Recognizing the multifaceted nature of language phenomena and the need for interdisciplinary expertise, CLiC-it aims to bring together researchers from different fields including Computational Linguistics and Natural Language Processing, Linguistics, Cognitive Science, Machine Learning, Computer Science, Knowledge Representation, Information Retrieval, and Digital Humanities. CLiC-it welcomes contributions focusing on all languages, with a particular emphasis on Italian.
The “Language Understanding in the Human-Machine Era” (LUHME) workshop aims to reignite, retrieve, resume, and refocus the enduring debate about the role of understanding in natural language use and related applications. Specifically, it seeks to elucidate the nature of language understanding and ascertain whether it is indispensable for computational natural language tasks such as automated translation and natural language generation. Furthermore, it aims to provide insight into the role played by language professionals (e.g., linguists, professional translators, interpreters, language educators) in computational natural language understanding. It will, therefore, convene researchers interested in the intersection of language understanding and the effective use of language technologies in human-machine interaction.
SemEval is a series of international natural language processing (NLP) research workshops whose mission is to advance the current state of the art in semantic analysis and to help create high-quality annotated datasets in a range of increasingly challenging problems in natural language semantics. Each year’s workshop features a collection of shared tasks in which computational semantic analysis systems designed by different teams are presented and compared.