mlsanityData to 14 Oct 2026

U4RASD at KnowledgeGraphEval-2026: Ontology-Constrained Encoder and LLM Systems for Arabic Relation Extraction

arXiv 2610.12742 ↗First posted 8 Oct 2026cs.CLcited by 0

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Abstract (arXiv)

This paper details our submission to KnowledgeGraphEval 2026 Subtask 2 on directed Arabic relation extraction. We explored encoder-based and large language model approaches for predicting one of 40 relations or no_relation from an Arabic sentence and a subject-object pair. Our encoder systems use typed entity markers and separate relation-existence and relation-classification heads, while our LLM systems fine-tune Yehia and Qwen3.5 with QLoRA and ontology-constrained prediction. Our best system, an ensemble of Yehia-RE, Qwen-RE, and TypedPair, achieved a micro-F1 score of 94.06 and ranked 1st in Subtask 2. Yehia-RE (full-vocabulary) achieved 92.98, while the best encoder and Qwen-RE achieved 92.69 and 91.94 respectively. Our results highlight the importance of constrained prediction and complementary modeling approaches for Arabic relation extraction.

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References · 11

  1. 2020AraBERT: Transformer-based Model for Arabic Language Understandingcited by 362
  2. 2019Matching the Blanks: Distributional Similarity for Relation Learningcited by 272
  3. 2023A Rank Stabilization Scaling Factor for Fine-Tuning with LoRAcited by 243
  4. 2023Revisiting Relation Extraction in the era of Large Language Modelscited by 102
  5. 2021An Improved Baseline for Sentence-level Relation Extractioncited by 81
  6. 2022ORCA: A Challenging Benchmark for Arabic Language Understandingcited by 47
  7. 2023Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractorscited by 45
  8. 2022Wojood: Nested Arabic Named Entity Corpus and Recognition using BERTcited by 33
  9. 2023Arabic Fine-Grained Entity Recognitioncited by 7
  10. 2025Konooz: Multi-domain Multi-dialect Corpus for Named Entity Recognitioncited by 3
  11. 2026AraModernBERT: Transtokenized Initialization and Long-Context Encoder Modeling for Arabiccited by 2

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