System Paper
A 6-page ACL-style paper describing the system, submitted via OpenReview, including public code on GitHub.
NLP/CORE Unranked
LM-KBC 2026
Workshop on Automated Knowledge Base Construction 2026 - LM-KBC - Shared Task
LM-KBC 2026 is the 5th edition of the AKBC Shared Task, co-located with EMNLP 2026 in Budapest, focusing on predicting complete knowledge base entries using language models. Participants must generate accurate object strings for six relations given subject-relation pairs, under strict closed-book and parameter budget constraints, with evaluation based on string matching and numeric tolerance.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Research areas in scope
01
Task Focus
Predicting complete knowledge base entries from language modelsClosed-book knowledge extractionString-based object predictionMulti-step and agentic inferenceNumeric and set-valued relation prediction
Policies worth checking twice
- Single-blind review
- Maximum 32B total neural parameters across all inference-time models
- Quantization does not reduce counted parameter size
- MoE models counted by total published parameters, not active ones
- No web search, RAG, external corpora, or KB lookup allowed
- No additional training, fine-tuning, or continued pretraining permitted
- Non-neural components (e.g., rule-based filtering, deduplication) are allowed
- Predictions must be submitted in JSONL format with ObjectEntities as strings
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026