Knowledge and Natural Language Processing Track @ ACM-SAC

Aim of the Knowledge and Natural Language Processing (KNLP) track at ACM SAC is to investigate techniques and application of knowledge engineering and natural language processing, focusing in particular on approaches combining them. This is an extremely interdisciplinary emerging research area, at the core of Artificial Intelligence, combining and complementing the scientific results from Natural Language Processing and Knowledge Representation and Reasoning.





Topics of interest

Topics of interest include, but are not limited to:

Natural Language Processing
NLP tasks for Knowledge Extraction
NLP for Ontology Population and Learning
Sentiment Analysis and Opinion Mining for Knowledge Applications
Interplay between Language and Ontologies
NLP for Explainable Knowledge
Machine Translation techniques for Multilingual Knowledge
NLP for the Web
Bias detection and mitigation in small/large LM
(Small/Large) LM and Knowledge
Knowledge
Knowledge to improve NLP tasks
Knowledge for Information Retrieval
Knowledge-based Sentiment Analysis and Opinion Mining
Combining Knowledge and Deep Learning for NLP
Knowledge for Text Summarization and Generation
Knowledge for Persuasion
Knowledge-based Machine Translation
Knowledge for the Web
Linked Data for NLP
Knowledge-based NL Explainability
LM-enhanced ontology and knowledge engineering methodologies and tools
LM-based agent for knowledge extraction, reasoning, and management
Ontology evaluation via small/large LMs
(Ontological) knowledge memorization in LMs
Knowledge-based techniques for LMs (Retrieval Augmented Generation based approaches, fact-checking, and bias mitigation)
Question answering over knowledge graphs via small/large LMs
Real-world applications that exploit Knowledge and NLP
Real-world applications that exploit Knowledge and NLP
Knowledge and NLP Systems for Big Data scenarios
Knowledge and NLP technology for a diverse, equitable, and inclusive society
Deployment of Knowledge and NLP Systems in specific domains, such as:
Digital Humanities and Social Sciences
eGovernment and public administration
Life sciences, health, and medicine
News and Data Streaming



Paper Submission

Submissions must not have been published or be concurrently considered for publication elsewhere. Papers should be submitted in PDF using the ACM-SAC proceedings format. Authors' names and affiliations should be entered separately at the submission site and not appear in the submitted papers. Each submission will be reviewed in a DOUBLE-BLIND process according to the ACM-SAC Regulations. Student Research Competition (SRC) submissions are welcome (see SAC 2026 SRC page for details).

Initial Submission Policy

All submissions must initially be submitted as regular papers. There is no separate submission track for poster papers.
Paper selection is based on originality, technical contribution, presentation quality, and relevance to the Knowledge and Natural Language Processing Track.
Based on the outcome of the review process, some submissions—although technically sound—may not be accepted as regular papers due to overall acceptance rate constraints, and could be accepted as posters

Minimum Length for Review Consideration

While there is no formal minimum page requirement, submissions of fewer than four (4) full pages that do not demonstrate substantial contributions may be subject to desk rejection without external review.

Camera-ready Page Limits

Regular Papers (accepted for publication):
Up to eight (8) pages are included with standard registration.

Poster Papers (recommended for acceptance):

Up to two (2) pages are included with standard registration.



Important Dates (check SAC website for up-to-date dates)

September 26, 2025: Regular Paper & SRC Abstract Submission





For further information, please visit the Knowledge and Natural Language Processing Track and ACM-SAC 2026 conference websites or feel free to contact the Track Co-Chairs.