*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 https://www.sigapp.org/sac/sac2026/authorkit.php. 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 https://www.sigapp.org/sac/sac2026/src_program.php).
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 https://www.sigapp.org/sac/sac2026/#important-dates 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 https://knlp.fbk.eu/ and ACM-SAC 2026 https://www.sigapp.org/sac/sac2026/ conference websites or feel free to contact the Track Co-Chairs knlp@fbk.eu.