Call for Papers

3rd Conference on Automated Knowledge Base Construction (AKBC)
October 4-8, 2021, Monday-Friday (held virtually)

Key dates

  • Paper submission deadline: June 21, 2021
  • Author response period: July 23-30, 2021
  • Notification of acceptance: Aug 18, 2021
  • Camera-ready papers due: September 15, 2021
  • Conference & workshop dates: Monday-Friday, October 4-8, 2021

All deadlines are 11.59 pm UTC -12h (“anywhere on Earth”).

Knowledge Base Construction

Knowledge gathering, representation, and reasoning are among the fundamental challenges of artificial intelligence. Large-scale repositories of knowledge about entities, relations, and their abstractions are known as “knowledge bases”. Most major technology companies now have substantial efforts in knowledge base construction. Related scholarly work spans many research areas, including machine learning, natural language processing, computer vision, information integration, databases, search, data mining, knowledge representation, human computation, human-computer interfaces, and fairness. The AKBC conference serves as a research forum for gathering all these areas, in both academia and industry.

About the Conference

Nearly a decade after the first AKBC workshop in Grenoble, France, 2010, AKBC became a conference in 2019. Why a stand-alone conference?

  • Long-standing and growing interest in the area.
  • We want to grow and connect the community beyond existing individual conference communities, bringing together ML, NLP, DB, IR, KRR, semantics, reasoning, common sense, QA, human computation, dialog, and HCI.
  • We want to set our own culture, including reviewing practices, and meeting format.
  • Why now? Growing interest across many areas. Disconnect among multiple relevant communities. Growing industry and government interest. Many of the long-existing conferences have grown uncomfortably large; a new, smaller conference can be more intimate, hospitable, and supportive.

Call for Papers

We invite the submission of papers describing previously unpublished research, including new methodology, datasets, evaluations, surveys, reproduced results, negative results, and visionary positions.

Topics of interest include, but are not limited to:

  • Natural language processing, information extraction, extraction of entities, relations, and events, semantic parsing, coreference, machine reading, entailment, web mining, multilingual NLP.
  • Information integration, entity resolution, schema & ontology alignment, text and structure alignment, federated KBs, Semantic Web.
  • Machine learning, supervised, unsupervised, lightly-supervised and distantly-supervised learning, deep learning, symbolic learning, multimodal learning, embeddings of knowledge.
  • Search, question-answering, reasoning, knowledge base completion, queries on mixtures of structured and unstructured data; querying under uncertainty.
  • Multi-modal knowledge bases: structured data, text, images, video, audio.
  • Human-computer interaction, crowdsourcing, interactive learning.
  • Fairness, accountability, transparency, misinformation, multiple viewpoints, uncertainty.
  • Databases, probabilistic databases, distributed databases, database cleaning, scalable computation, distributed computation, dynamic data, online adaptation of knowledge.
  • Systems, languages and toolkits, demonstrations of existing knowledge bases.
  • Evaluation of AKBC, datasets, evaluation methodology.

Authors of accepted papers will have the option for their conference paper to be archival (with full text in AKBC Proceedings, and be considered for best paper awards) or non-archival (listed in AKBC Conference schedule, with full text in OpenReview, and the flexibility to also submit elsewhere). Double-blind reviewing will be performed on the OpenReview platform, with papers, reviews and comments publicly visible.

Papers should be restricted to 10 single-column pages, excluding references. Appendices should be put after references and submitted in one PDF document. We also encourage authors to upload their code and data (<=100 Mb) as part of their supplementary material in order to help reviewers assess the quality of the work. Like submissions, supplementary material must be anonymized.

All submissions must be formatted with LaTeX using the following LaTeX source:

Submission site:

Dual Submission Policy: Submissions that are identical (or substantially similar) to versions that have been previously published, or accepted for publication, are not allowed and violate our dual submission policy. However, papers that cite previous related work by the authors and papers that have appeared on non-peered reviewed websites (like arXiv) or that have been presented at workshops (i.e., venues that do not have publication proceedings) do not violate the policy. The policy is enforced during the whole reviewing process.

Under-review Submissions: For papers that are under review in another conference (e.g., EMNLP 2021), you can submit your paper to AKBC but must use the non-archival option. In addition, please also adhere to the rules set by the other conference. Specifically for EMNLP 2021, we will respect EMNLP’s anonymization period and will publicly announce AKBC accepted papers (archival and non-archival) after EMNLP notifications on Aug 25.

Invited Talks

The following are confirmed invited speakers. Additional speakers are expected to be added.

Peter Clark, Allen Institute for AI
Jia Deng, Princeton
Greg Durrett, University of Texas Austin
Yolanda Gil, USC
Hanna Hajishirzi, University of Washington
Tim Kraska, MIT
Monica Lam, Stanford
Percy Liang, Stanford
Devi Parikh, Georgia Tech and Facebook AI Research
Sujith Ravi, SliceX AI
Siva Reddy, McGill
Dafna Shahaf, Hebrew University
David Sontag, MIT


In addition to the conference program, we will have a one-day collection of workshops on focused topics.


General Co-Chair
Andrew McCallum, University of Massachusetts Amherst, USA
General Co-Chair
Sameer Singh, University of California, Irvine, USA
Program Co-Chair
Danqi Chen, Princeton University
Program Co-Chair
Jonathan Berant, Tel Aviv University / Allen Institute for AI
Workshop Co-Chair
Eunsol Choi, UT Austin
Workshop Co-Chair
Waleed Ammar, Google
Virtual Platform Chair
Matt Gardner, Allen Institute for AI, USA
Website Chair
Maor Ivgi, Tel Aviv University

Area Chairs

Yael Amsterdamer, Bar-Ilan University
Bhavana Dalvi, Allen Institute for Artificial Intelligence
Greg Durrett, UT Austin
Robin Jia, Facebook AI Research / University of Southern California
Gerard de Melo, Hasso Plattner Institute / University of Potsdam
Barbara Plank, IT University of Copenhagen
Alex Ratner, University of Washington
Partha Talukdar, Indian Institute of Science, Bangalore
Chenhao Tan, University of Chicago
Jian Tang, MILA/HEC Montreal
Jesse Thomason, University of Southern California
Andreas Vlachos, University of Cambridge
Diyi Yang, Georgia Institute of Technology

Questions? Please mail: