Orna Grumberg
E258561
Orna Grumberg is a prominent computer scientist known for her contributions to formal verification and model checking.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Orna Grumberg canonical | 5 |
How this entity was disambiguated
This entity first appeared as the object of triple T2169592 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orna Grumberg Context triple: [Edmund M. Clarke, coAuthor, Orna Grumberg]
-
A.
Einat Kalisch-Rotem
Einat Kalisch-Rotem is an Israeli urban planner and politician who became the first female mayor of Haifa.
-
B.
Rachel Cohen-Kagan
Rachel Cohen-Kagan was an Israeli politician, women's rights activist, and one of the signatories of Israel's Declaration of Independence.
-
C.
Orly Sud
Orly Sud is the former name of Orly 4, a terminal facility at Paris Orly Airport in France.
-
D.
Ayelet Zurer
Ayelet Zurer is an Israeli actress known internationally for her roles in films such as "Angels & Demons," "Munich," and "Man of Steel."
-
E.
Marla Lerner Tanenbaum
Marla Lerner Tanenbaum is an American philanthropist and baseball executive best known as a principal owner of the Washington Nationals and for her leadership in charitable and community initiatives.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Orna Grumberg Target entity description: Orna Grumberg is a prominent computer scientist known for her contributions to formal verification and model checking.
-
A.
Einat Kalisch-Rotem
Einat Kalisch-Rotem is an Israeli urban planner and politician who became the first female mayor of Haifa.
-
B.
Rachel Cohen-Kagan
Rachel Cohen-Kagan was an Israeli politician, women's rights activist, and one of the signatories of Israel's Declaration of Independence.
-
C.
Orly Sud
Orly Sud is the former name of Orly 4, a terminal facility at Paris Orly Airport in France.
-
D.
Ayelet Zurer
Ayelet Zurer is an Israeli actress known internationally for her roles in films such as "Angels & Demons," "Munich," and "Man of Steel."
-
E.
Marla Lerner Tanenbaum
Marla Lerner Tanenbaum is an American philanthropist and baseball executive best known as a principal owner of the Washington Nationals and for her leadership in charitable and community initiatives.
- F. None of above. chosen
Statements (25)
| Predicate | Object |
|---|---|
| instanceOf |
academic
ⓘ
computer scientist ⓘ |
| awardReceived | CAV Award ⓘ |
| coAuthorOf |
Model Checking
ⓘ
linked to:
Model Checking (book)
|
| coAuthorWith |
Doron A. Peled
ⓘ
linked to:
Doron Peled
Edmund M. Clarke ⓘ |
| countryOfCitizenship | Israel ⓘ |
| employer | Technion – Israel Institute of Technology ⓘ |
| fieldOfWork |
abstraction in model checking
ⓘ
compositional verification ⓘ computer science ⓘ formal verification ⓘ model checking ⓘ temporal logic ⓘ verification of reactive systems ⓘ |
| knownFor |
contributions to formal verification
ⓘ
contributions to model checking ⓘ |
| languageSpoken |
English
ⓘ
Hebrew ⓘ |
| memberOf |
Academia Europaea
ⓘ
European Association for Theoretical Computer Science ⓘ |
| notableWork |
research on abstraction-refinement in model checking
ⓘ
research on compositional model checking ⓘ |
| occupation | professor ⓘ |
| workLocation | Haifa ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Orna Grumberg Description of subject: Orna Grumberg is a prominent computer scientist known for her contributions to formal verification and model checking.
Referenced by (5)
Full triples — surface form annotated when it differs from this entity's canonical label.