word sense disambiguation

We are delighted to announce SemEval-2026 Task 5: Rating Plausibility of Word Senses in Ambiguous Sentences through Narrative Understanding.

Word Sense Disambiguation tasks commonly assume that only one word sense is "correct", but this does not always reflect how humans perceive meaning. Ambiguity, underspecification and subjective factors such as individual linguistic experience can influence which word senses are perceived as plausible in a given context. For these reasons, human intuitions and model predictions may frequently diverge.

Natural language understanding (NLU) is a core aspect of natural language processing (NLP), facilitating semantics-based human-machine interactions. One of the key challenges in Arabic is ambiguity, that is because Arabic exhibits morphological richness, encompassing a complex interplay of roots, stems, and affixes, rendering words susceptible to multiple interpretations based on their morphology. Ambiguity in language can lead to misunderstandings, incorrect interpretations, and errors in NLP applications. A core NLU task is Word Sense Disambiguation (WSD), and its special case Location Mention Disambiguation (LMD). WSD aims to determine the correct sense of ambiguous words in context, while LMDfocuses on disambiguating location mention that is referred to with multiple toponyms, i.e., particular places or locations. Both tasks are vital in NLP and information retrieval, as it helps to correctly interpret and extract information from text. In this shared-task we introduce two subtasks, WSD and LMD.

Greeting
We would like to extend an invitation to participate in the KSAA-CAD: Contemporary Arabic Dictionary Shared Task! For Reverse Dictionary and Word Sense Disambiguation at ArabicNLP 2024!
Please find all the necessary information below.
https://arai.ksaa.gov.sa/sharedTask2024/

Registration deadline: 29th of April 2024.

New trends of intelligent language processing systems are emerging, such as big data analysis, social network analysis, Internet of things, smart services, mobile computing, computer games, to name a few. Applications of these trends have been applied to various domains including education, travel and tourism, healthcare, among others.

New trends of intelligent language processing systems are emerging, such as big data analysis, social network analysis, Internet of things, smart services, mobile computing, computer games, to name a few. Applications of these trends have been applied to various domains including education, travel and tourism, healthcare, among others.

APOLOGIES FOR CROSS POSTING

SemEval-3
6th International Workshop on Semantic Evaluations

2nd Call for Task Proposals - Extended Deadline

The SemEval Programme committee invites proposals for tasks to be run as part of SemEval-3. We welcome tasks that can test an automatic system for semantic analysis of text, be it application dependent or independent. We especially welcome tasks for different languages and cross-lingual tasks.

For SemEval-3 we particularly encourage the following aspects in task design:

Reuse of existing annotations and training data

Call for Task Proposals

The SemEval Programme committee invites proposals for tasks to be run as part of SemEval-3. We welcome tasks that can test an automatic system for semantic analysis of text, be it application dependent or independent. We especially welcome tasks for different languages and cross-lingual tasks.

For SemEval-3 we particularly encourage the following aspects in task design:

Reuse of existing annotations and training data