CfP Special Issue: NLP and Semantics

Special Issue Guest Editors:

Daniel Hershcovich, Lucia Donatelli and Stephan Oepen

Making computers as intelligent as humans has been argued to be as difficult as making them understand human language, which is one of the focus points of Natural Language Processing (NLP). The field has been changing over the past decades, generally moving from rule-based methods to statistical ones. Machine learning (ML) methods, in particular deep learning, are today omnipresent, challenging methods based on linguistic theories by fully end-to-end data-driven modeling. However, combining powerful ML models with flexible pipelines and frameworks based on human and linguistic insight is an exciting development promising the best of both worlds.

NLP applications are abundant, and are already changing people’s lives, enabling effortless translation, learning and interaction with human-centric systems in robotics and virtual assistants. While many classical NLP problems deal with modeling the surface form of linguistic utterances, general natural language understanding and generation depend on explicit or implicit modeling of semantics, including meaning, communicative intent, and the complex mapping to the linguistic form. Computational semantics is the study of how to automate the process of constructing and reasoning with meaning representations of natural language expressions, which can take many forms, such as continuous vectors or discrete graphs.

For this special issue, we welcome contributions including, but not limited to the following topics: lexical semantics, compositional semantics, cross-lingual semantics, semantic parsing, syntax-semantics interface, semantic role labeling, textual inference, formal semantics, coreference, discourse, reading comprehension, knowledge acquisition, common sense reasoning, summarization, multimodal semantics, semantic annotation, ethical aspects in semantic representations, underspecification, ontologies, sentiment analysis, stylistic analysis, argument mining, and human-robot interaction

Contributions can be from the following categories (for more detailed information please refer to the author instructions for each of these categories):

Technical Contribution; System Descriptions; Project Reports; Dissertation and Habilitation Abstracts; AI Transfer; Discussion

If you are interested in submitting a paper please contact one of the guest editors:

Daniel Hershcovich, University of Copenhagen, Denmark (

Lucia Donatelli, Saarland University, Germany (

Stephan Oepen, University of Oslo, Norway (

Handling Editor, Editorial Board:

Christian Igel, University of Copenhagen, Denmark (

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