Call for papers KNLP@ACM-SA

PB
Patrizio Bellan
Wed, Aug 19, 2026 12:24 PM

Knowledge and Natural Language Processing Track @ ACM SAC 2027

Aim and Scope

The Knowledge and Natural Language Processing (KNLP) Track at the ACM
Symposium on Applied Computing investigates methods and applications at the
intersection of Knowledge Engineering and Natural Language Processing,
with particular emphasis on approaches that combine these two areas.

KNLP is an emerging and highly interdisciplinary research field at the core
of Artificial Intelligence. It brings together and complements scientific
advances in Natural Language Processing, Knowledge Representation and
Reasoning, Machine Learning, and related disciplines.

Topics of Interest

Topics of interest include, but are not limited to, the following.

Natural Language Processing

  • NLP methods for knowledge extraction
  • NLP for ontology population and ontology learning
  • Sentiment analysis and opinion mining for knowledge-based applications
  • Interplay between natural language and ontologies
  • NLP for explainable knowledge
  • Machine translation techniques for multilingual knowledge
  • NLP for the Web
  • Bias detection and mitigation in small and large language models
  • Interaction between small or large language models and knowledge

Knowledge

  • Knowledge-enhanced NLP
  • Knowledge for information retrieval
  • Knowledge-based sentiment analysis and opinion mining
  • Combining knowledge and deep learning for NLP
  • Knowledge technologies for the Web
  • Knowledge-enhanced agentic reasoning
  • Agent reasoning over knowledge graphs and ontologies
  • Knowledge-based agent personalization
  • Linked Data for NLP
  • Knowledge-based natural language explainability
  • Language-model-enhanced ontology and knowledge engineering
    methodologies and tools
  • Language-model-based agents for knowledge extraction, reasoning, and
    management
  • Ontology evaluation using small and large language models
  • Ontological knowledge representation and memorization in language
    models
  • Knowledge-based techniques for language models, including
    Retrieval-Augmented Generation, fact-checking, and bias mitigation
  • Question answering over knowledge graphs using small and large
    language models

Real-World Applications Exploiting Knowledge and NLP

  • Knowledge and NLP systems for Big Data scenarios
  • Knowledge and NLP technologies supporting a diverse, equitable, and
    inclusive society
  • Deployment and evaluation of Knowledge and NLP systems in domains such
    as:
    • Digital Humanities and Social Sciences
    • eGovernment and public administration
    • Life sciences, healthcare, and medicine
    • News, media, and data-streaming environments

Paper Submission

We invite original research papers and experience reports addressing the
topics listed above.

Submissions must not have been previously published or be under
consideration for publication elsewhere. Papers must be submitted in PDF
format using the official ACM SAC proceedings template.

Authors’ names and affiliations must be entered separately in the
submission system and must not appear in the submitted manuscript. All
submissions will undergo a double-blind peer-review process in accordance
with ACM SAC regulations.

Submissions to the Student Research Competition (SRC) are also welcome.
Prospective authors should consult the SAC 2027 SRC page for eligibility
requirements and submission instructions.

Submission Policy

  • All papers must initially be submitted as regular papers. There is
    no separate submission category for poster papers.
  • Papers will be evaluated according to their originality, technical
    contribution, presentation quality, and relevance to the Knowledge and
    Natural Language Processing Track.
  • Depending on the outcome of the review process and the overall
    acceptance-rate constraints, technically sound submissions that cannot be
    accepted as regular papers may be offered acceptance as posters.
  • Although there is no formal minimum page requirement, submissions
    shorter than four full pages that do not demonstrate a substantial
    contribution may be desk-rejected without external review.

Submission Links

Important Dates

Please consult the official ACM SAC 2027 website
https://www.sigapp.org/sac/sac2027/#important-dates for up-to-date
deadlines and possible changes.

  • October 2, 2026: Regular paper and SRC abstract submission
  • November 13, 2026: Author notification
  • November 28, 2026: Camera-ready copies of accepted papers and SRC
    submissions
  • December 5, 2026: Author registration deadline
  • April 5–9, 2027: Knowledge and Natural Language Processing Track at
    ACM SAC 2027

All deadlines follow the time zone specified on the official conference
website.

Further Information

For further information, please visit the Knowledge and Natural Language
Processing Track website https://knlp.fbk.eu/ and the ACM SAC 2027
conference website https://www.sigapp.org/sac/sac2027/.

Questions may be addressed to the KNLP Track Co-Chairs knlp@fbk.eu.

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*Knowledge and Natural Language Processing Track @ ACM SAC 2027* *Aim and Scope* The Knowledge and Natural Language Processing (KNLP) Track at the ACM Symposium on Applied Computing investigates methods and applications at the intersection of *Knowledge Engineering* and *Natural Language Processing*, with particular emphasis on approaches that combine these two areas. KNLP is an emerging and highly interdisciplinary research field at the core of Artificial Intelligence. It brings together and complements scientific advances in Natural Language Processing, Knowledge Representation and Reasoning, Machine Learning, and related disciplines. *Topics of Interest* Topics of interest include, but are not limited to, the following. *Natural Language Processing* - NLP methods for knowledge extraction - NLP for ontology population and ontology learning - Sentiment analysis and opinion mining for knowledge-based applications - Interplay between natural language and ontologies - NLP for explainable knowledge - Machine translation techniques for multilingual knowledge - NLP for the Web - Bias detection and mitigation in small and large language models - Interaction between small or large language models and knowledge *Knowledge* - Knowledge-enhanced NLP - Knowledge for information retrieval - Knowledge-based sentiment analysis and opinion mining - Combining knowledge and deep learning for NLP - Knowledge technologies for the Web - Knowledge-enhanced agentic reasoning - Agent reasoning over knowledge graphs and ontologies - Knowledge-based agent personalization - Linked Data for NLP - Knowledge-based natural language explainability - Language-model-enhanced ontology and knowledge engineering methodologies and tools - Language-model-based agents for knowledge extraction, reasoning, and management - Ontology evaluation using small and large language models - Ontological knowledge representation and memorization in language models - Knowledge-based techniques for language models, including Retrieval-Augmented Generation, fact-checking, and bias mitigation - Question answering over knowledge graphs using small and large language models *Real-World Applications Exploiting Knowledge and NLP* - Knowledge and NLP systems for Big Data scenarios - Knowledge and NLP technologies supporting a diverse, equitable, and inclusive society - Deployment and evaluation of Knowledge and NLP systems in domains such as: - Digital Humanities and Social Sciences - eGovernment and public administration - Life sciences, healthcare, and medicine - News, media, and data-streaming environments *Paper Submission* We invite original research papers and experience reports addressing the topics listed above. Submissions must not have been previously published or be under consideration for publication elsewhere. Papers must be submitted in PDF format using the official ACM SAC proceedings template. Authors’ names and affiliations must be entered separately in the submission system and must not appear in the submitted manuscript. All submissions will undergo a *double-blind peer-review process* in accordance with ACM SAC regulations. Submissions to the *Student Research Competition (SRC)* are also welcome. Prospective authors should consult the SAC 2027 SRC page for eligibility requirements and submission instructions. *Submission Policy* - All papers must initially be submitted as *regular papers*. There is no separate submission category for poster papers. - Papers will be evaluated according to their originality, technical contribution, presentation quality, and relevance to the Knowledge and Natural Language Processing Track. - Depending on the outcome of the review process and the overall acceptance-rate constraints, technically sound submissions that cannot be accepted as regular papers may be offered acceptance as posters. - Although there is no formal minimum page requirement, submissions shorter than *four full pages* that do not demonstrate a substantial contribution may be desk-rejected without external review. *Submission Links* - *Regular papers and SRC abstracts:* submission links are available through the ACM SAC 2027 website <https://www.sigapp.org/sac/sac2027/> - *Author kit and templates:* formatting instructions and official templates are available through the ACM SAC 2027 website <https://www.sigapp.org/sac/sac2027/> *Important Dates* Please consult the official ACM SAC 2027 website <https://www.sigapp.org/sac/sac2027/#important-dates> for up-to-date deadlines and possible changes. - *October 2, 2026:* Regular paper and SRC abstract submission - *November 13, 2026:* Author notification - *November 28, 2026:* Camera-ready copies of accepted papers and SRC submissions - *December 5, 2026:* Author registration deadline - *April 5–9, 2027:* Knowledge and Natural Language Processing Track at ACM SAC 2027 All deadlines follow the time zone specified on the official conference website. *Further Information* For further information, please visit the Knowledge and Natural Language Processing Track website <https://knlp.fbk.eu/> and the ACM SAC 2027 conference website <https://www.sigapp.org/sac/sac2027/>. Questions may be addressed to the KNLP Track Co-Chairs <knlp@fbk.eu>. -- -- Le informazioni contenute nella presente comunicazione sono di natura  privata e come tali sono da considerarsi riservate ed indirizzate  esclusivamente ai destinatari indicati e per le finalità strettamente  legate al relativo contenuto. Se avete ricevuto questo messaggio per  errore, vi preghiamo di eliminarlo e di inviare una comunicazione  all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.