Hiba Arnaout

I'm a PhD candidate at the Max Planck Institute for Informatics, a member of the Databases and Information Systems Group (advisors: Prof. Gerhard Weikum and Dr. Simon Razniewski). I work on discovering informative negative statements from encyclopedic and commonsense open-world knowledge bases. During this work I visited The University of Edinburgh for 6 months and collaborated with Dr. Jeff Z. Pan. I interned at Bosch Center for Artificial Intelligence (mentor: Dr. Daria Stepanova) for 4 months, working on repairing inconsistent knowledge bases using pretrained language models. Previously, I received my Master's of Computer Science from The American University of Beirut (advisor: Dr. Shady Elbassuoni, topic: effective search of RDF Knowledge Bases).

My research interests include knowledge bases, negative knowledge, information retrieval. [Research statement] [CV]


(newest to oldest)

Completeness, Recall, and Negation in Open-World Knowledge Bases: A Survey.
Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, and Fabian Suchanek
CSUR 2023 under review

In this survey we discuss how knowledge about completeness, recall, and negation in KBs can be expressed, extracted, and inferred.


journal paper

Wiki-based Communities of Interest: Demographics and Outliers.
Hiba Arnaout, Simon Razniewski, and Jeff Z. Pan
ICWSM 2023

Identified from Wikidata, we construct a datasets about 7.5k communities of interest such as The White House Coronavirus Task Force, covering 345k subjects. Every community comes with interseting findings such as demographic data and exceptional members.


dataset paper

UnCommonSense in Action! Informative Negations for Commonsense Knowledge Bases.
Hiba Arnaout, Tuan-Phong Nguyen, Simon Razniewski, and Gerhard Weikum
WSDM 2023

We present a web portal to showcase the Uncommonsense system. Users can browse interesting negative statements about every day concepts such as elephant, pancake, and acne.


demo paper

UnCommonSense: Informative Negative Knowledge about Everyday Concepts.
Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
CIKM 2022 Acceptance rate 23%

We introduce UnCommonSense, a method for discovering expressive negative statements about everyday concepts. The method significantly outperforms the state-of-the-art on informativeness and recall.


conference paper

Utilizing Language Model Probes for Knowledge Graph Repair.
Hiba Arnaout, Trung-Kien Tran, Daria Stepanova, Mohamed Hassan Gad-Elrab, Simon Razniewski, and Gerhard Weikum
Wikiworkshop at WWW 2022

We present a method to repair incorrect statements in existing knowledge bases by replacing incorrect triples with likely correct ones, thus avoiding information loss. Our method explores the power of LM probes and shows that context retrieval from the knowledge base itself can significantly boost the probing.


workshop paper

Negative Statements Considered Useful.
Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
JWS 2021

We extend previous methods on negation inference by introducing the order-oriented peer-based inference method, which shows an improvement in informativeness.


journal paper

Negative Knowledge for Open-world Wikidata.
Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
WWW Companion 2021

We review Wikidata's attempts to allow negative knowledge and discuss the gains challenges arising from implementing a negation-inference system.


workshop paper

Neguess: Wikidata-entity Guessing Game with Negative Clues.
Aditya B. Biswas, Hiba Arnaout, and Simon Razniewski
ISWC 2021

We publish an guessing game with unique emphasis on challenging negative clues, e.g., a famous English physicist who has never won a Nobel Prize in Physics?


demo paper

Wikinegata: A Knowledge Base with Interesting Negative Statements.
Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
VLDB 2021

A web platform for exploring interesting negative statements about 600k encyclopedic entities.


demo paper

Enriching Knowledge Bases with Interesting Negative Statements.
Hiba Arnaout, Simon Razniewski, and Gerhard Weikum

The first publication of my PhD, this work introduces the topic of discovering salient negative statements in open-world knowledge bases and proposes to infer candidates from encyclopedic knowledge bases as well as query logs.

AKBC 2020 Audience-choice best paper award (voted by conference attendees)

conference paper

Biological Knowledge Graph Construction, Search, and Navigation.
Chandana Tennakoon, Nazar Zaki, Hiba Arnaout, Shady Elbassuoni, Wassim El-Hajj, and Alanoud Al Jaberi
Academic Press 2019

In this book on leveraging biomedical and healthcare data, my contribution is in the writing of chapter 7 on biological knowledge graph construction and search.


book chapter

Effective Searching of RDF Knowledge Graphs.
Hiba Arnaout and Shady Elbassuoni
JWS 2018 Later presented at ISWC 2018

This publication summarizes my Master thesis. It proposes a framework for searching knowledge graphs using keyword-augmented SPARQL queries and ranking results by both relevance and novelty.


journal paper

Top-k Keyword Search over Wikipedia-based RDF Knowledge Graphs.
Hrag Yoghourdjian, Shady Elbassuoni, Mohamad Jaber, and Hiba Arnaout
KDIR 2017 Best student paper award nominee

This work proposes a novel retrieval model for general keyword queries over the YAGO knowledge graph.


conference paper

Result Diversity for RDF Search.
Hiba Arnaout and Shady Elbassuoni
KDIR 2016

This paper proposes a method to diversify the results of triple-pattern queries over RDF datasets..


conference paper


  • Enriching Open-world Knowledge Graphs with Salient Negative Statements, invited talk at the L3S Research Center, 2023. [SLIDES]
  • Negative Statements Considered Useful, invited talk at the Institute for Language, Cognition and Computation (ILCC), The University of Edinburgh, 2022. [SLIDES]
  • Completeness, Recall, and Negation in Open-World Knowledge Bases (with Simon Razniewski, Shrestha Ghosh, and Fabian Suchanek), tutorial at KR 2021, ISWC 2021, and WWW 2022. [WEBPAGE]
  • On the Limits of Machine Knowledge (with Simon Razniewski, Shrestha Ghosh, and Fabian Suchanek), tutorial at VLDB 2021. [WEBPAGE]
  • Enriching Knowledge Bases with Interesting Negative Statements, Forum for presentations of significant Semantic Web-related research at ISWC 2020.


  • Researcher
    Max Planck Institute for Informatics
    Feb 2018 - exp. May 2023
    Saarbrücken, Germany
  • Research Intern
    Bosch Center for Artificial Intelligence
    Jun 2021 - Mar 2022
    Renningen, Germany
  • Visiting Researcher
    The University of Edinburgh
    Feb 2020 - Aug 2020
    Edinburgh, United Kingdom
  • Document Control Administrator
    American University of Beirut
    Jan 2016 – Dec 2017
    Beirut, Lebanon
  • Research Assistant
    American University of Beirut
    Feb 2014 – Jan 2018
    Beirut, Lebanon
  • IT Instructor
    American University of Beirut & United Nations
    Mar 2017 – Sep 2017
    Beirut, Lebanon
  • Teaching Assistant
    American University of Beirut
    Feb 2014 – Dec 2016
    Beirut, Lebanon


  • Reviewer: JWS ('22), EMNLP ('21,'22), IJCAI ('21,'22, '23), CIKM ('20,'21), ISWC ('20, '21), ACL ('20, '23).
  • Volunteer: VLDB ('21).

Scholarships and Awards
  • Reward for invention Knowledge Graph Repair Using Ontologies and LMs, Bosch, 2022.
  • Participated in discussion, DFG grant of 312,000 € for compiling negative knowledge at web scale, 2021.
  • Audience-choice Best Paper Award at AKBC, 2020.
  • Best Student Paper Award Nominee at IC3K'17, 2017.
  • Full Graduate Assistantship at the American University of Beirut, 2014.

Student Supervision
  • Aditya Bikram Biswas (Master's student), 2021.
  • Mang Zhao (Master's student), 2018.

Other Activities
  • Attended Reasoning Web Summer School, RW, 2019.
  • Attended Lisbon Machine Learning School, LxMLS, 2018.