@inproceedings{aljabari-etal-2026-knowledgegrapheval,
title = "{K}nowledge{G}raph{E}val 2026: The First Shared Task on {A}rabic Knowledge Graphs",
author = "Aljabari, Alaa and
Hamad, Nagham and
El Mekki, Abdellah and
Abdul-Mageed, Muhammad and
Zitouni, Imed and
Chawla, Sanjay and
Jarrar, Mustafa",
editor = "Abdul-Mageed, Muhammad and
Elsayed, Tamer and
Bouamor, Houda and
El-Beltagy, Samhaa and
Al-Khalifa, Hend and
Abdelali, Ahmed and
Elmadany, AbdelRahim and
El Mekki, Abdellah and
Darwish, Kareem and
Alkhereyf, Sakhar and
Luqman, Hamzah and
Khalifa, Salam and
Magdy, Samar and
Alyafeai, Zaid and
Hamed, Injy and
Zaghouani, Wajdi and
Zitouni, Imed",
booktitle = "Proceedings of The Fourth {A}rabic Natural Language Processing Conference: Shared Tasks",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.arabicnlp-sharedtasks.148/",
pages = "1182--1194",
ISBN = "979-8-89176-497-2",
abstract = "We present KnowledgeGraphEval 2026, the first Arabic shared task dedicated to knowledge graph (KG) construction from text. The task focuses on extracting named entities and semantic relations from Arabic text to build structured, machine-readable knowledge representations. It includes two subtasks: (i) \textbf{AdaptNER}, which evaluates cross-domain named entity recognition (NER), and (ii) \textbf{Relation Extraction (RE)}, which predicts semantic relations between predefined entity pairs. For AdaptNER, we release KONOOZ MSA, an Arabic NER benchmark annotated with 21 entity types across 10 domains. For RE, we release WojoodRelations, an Arabic RE dataset annotated with 40 relation types. At test time, 14 teams participated, of which 13 submitted system description papers, and one RE paper was subsequently rejected. The best systems achieve F1 scores of 76{\%} and 96{\%} on AdaptNER and RE, respectively. Results show that cross-domain NER remains challenging, while RE systems continue to face difficulties with rare and semantically confusable relations. We release the datasets, baselines, and evaluation tools for reproducible research in Arabic information extraction and KG construction."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="aljabari-etal-2026-knowledgegrapheval">
<titleInfo>
<title>KnowledgeGraphEval 2026: The First Shared Task on Arabic Knowledge Graphs</title>
</titleInfo>
<name type="personal">
<namePart type="given">Alaa</namePart>
<namePart type="family">Aljabari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nagham</namePart>
<namePart type="family">Hamad</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Abdellah</namePart>
<namePart type="family">El Mekki</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Muhammad</namePart>
<namePart type="family">Abdul-Mageed</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Imed</namePart>
<namePart type="family">Zitouni</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sanjay</namePart>
<namePart type="family">Chawla</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mustafa</namePart>
<namePart type="family">Jarrar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-10</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of The Fourth Arabic Natural Language Processing Conference: Shared Tasks</title>
</titleInfo>
<name type="personal">
<namePart type="given">Muhammad</namePart>
<namePart type="family">Abdul-Mageed</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tamer</namePart>
<namePart type="family">Elsayed</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Houda</namePart>
<namePart type="family">Bouamor</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Samhaa</namePart>
<namePart type="family">El-Beltagy</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hend</namePart>
<namePart type="family">Al-Khalifa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ahmed</namePart>
<namePart type="family">Abdelali</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">AbdelRahim</namePart>
<namePart type="family">Elmadany</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Abdellah</namePart>
<namePart type="family">El Mekki</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kareem</namePart>
<namePart type="family">Darwish</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sakhar</namePart>
<namePart type="family">Alkhereyf</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hamzah</namePart>
<namePart type="family">Luqman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Salam</namePart>
<namePart type="family">Khalifa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Samar</namePart>
<namePart type="family">Magdy</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Zaid</namePart>
<namePart type="family">Alyafeai</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Injy</namePart>
<namePart type="family">Hamed</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Wajdi</namePart>
<namePart type="family">Zaghouani</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Imed</namePart>
<namePart type="family">Zitouni</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Budapest, Hungary</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-497-2</identifier>
</relatedItem>
<abstract>We present KnowledgeGraphEval 2026, the first Arabic shared task dedicated to knowledge graph (KG) construction from text. The task focuses on extracting named entities and semantic relations from Arabic text to build structured, machine-readable knowledge representations. It includes two subtasks: (i) AdaptNER, which evaluates cross-domain named entity recognition (NER), and (ii) Relation Extraction (RE), which predicts semantic relations between predefined entity pairs. For AdaptNER, we release KONOOZ MSA, an Arabic NER benchmark annotated with 21 entity types across 10 domains. For RE, we release WojoodRelations, an Arabic RE dataset annotated with 40 relation types. At test time, 14 teams participated, of which 13 submitted system description papers, and one RE paper was subsequently rejected. The best systems achieve F1 scores of 76% and 96% on AdaptNER and RE, respectively. Results show that cross-domain NER remains challenging, while RE systems continue to face difficulties with rare and semantically confusable relations. We release the datasets, baselines, and evaluation tools for reproducible research in Arabic information extraction and KG construction.</abstract>
<identifier type="citekey">aljabari-etal-2026-knowledgegrapheval</identifier>
<location>
<url>https://aclanthology.org/2026.arabicnlp-sharedtasks.148/</url>
</location>
<part>
<date>2026-10</date>
<extent unit="page">
<start>1182</start>
<end>1194</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T KnowledgeGraphEval 2026: The First Shared Task on Arabic Knowledge Graphs
%A Aljabari, Alaa
%A Hamad, Nagham
%A El Mekki, Abdellah
%A Abdul-Mageed, Muhammad
%A Zitouni, Imed
%A Chawla, Sanjay
%A Jarrar, Mustafa
%Y Abdul-Mageed, Muhammad
%Y Elsayed, Tamer
%Y Bouamor, Houda
%Y El-Beltagy, Samhaa
%Y Al-Khalifa, Hend
%Y Abdelali, Ahmed
%Y Elmadany, AbdelRahim
%Y El Mekki, Abdellah
%Y Darwish, Kareem
%Y Alkhereyf, Sakhar
%Y Luqman, Hamzah
%Y Khalifa, Salam
%Y Magdy, Samar
%Y Alyafeai, Zaid
%Y Hamed, Injy
%Y Zaghouani, Wajdi
%Y Zitouni, Imed
%S Proceedings of The Fourth Arabic Natural Language Processing Conference: Shared Tasks
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-497-2
%F aljabari-etal-2026-knowledgegrapheval
%X We present KnowledgeGraphEval 2026, the first Arabic shared task dedicated to knowledge graph (KG) construction from text. The task focuses on extracting named entities and semantic relations from Arabic text to build structured, machine-readable knowledge representations. It includes two subtasks: (i) AdaptNER, which evaluates cross-domain named entity recognition (NER), and (ii) Relation Extraction (RE), which predicts semantic relations between predefined entity pairs. For AdaptNER, we release KONOOZ MSA, an Arabic NER benchmark annotated with 21 entity types across 10 domains. For RE, we release WojoodRelations, an Arabic RE dataset annotated with 40 relation types. At test time, 14 teams participated, of which 13 submitted system description papers, and one RE paper was subsequently rejected. The best systems achieve F1 scores of 76% and 96% on AdaptNER and RE, respectively. Results show that cross-domain NER remains challenging, while RE systems continue to face difficulties with rare and semantically confusable relations. We release the datasets, baselines, and evaluation tools for reproducible research in Arabic information extraction and KG construction.
%U https://aclanthology.org/2026.arabicnlp-sharedtasks.148/
%P 1182-1194
Markdown (Informal)
[KnowledgeGraphEval 2026: The First Shared Task on Arabic Knowledge Graphs](https://aclanthology.org/2026.arabicnlp-sharedtasks.148/) (Aljabari et al., ArabicNLP 2026)
ACL
- Alaa Aljabari, Nagham Hamad, Abdellah El Mekki, Muhammad Abdul-Mageed, Imed Zitouni, Sanjay Chawla, and Mustafa Jarrar. 2026. KnowledgeGraphEval 2026: The First Shared Task on Arabic Knowledge Graphs. In Proceedings of The Fourth Arabic Natural Language Processing Conference: Shared Tasks, pages 1182–1194, Budapest, Hungary. Association for Computational Linguistics.