John H. Tilelli Jr.
E138528
John H. Tilelli Jr. is a retired four-star U.S. Army general who served as Vice Chief of Staff of the Army and later commanded United States Forces Korea.
All labels observed (1)
| Label | Occurrences |
|---|---|
| John H. Tilelli Jr. canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1070384 — 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: John H. Tilelli Jr. Context triple: [Pennsylvania Military College, notableAlumni, John H. Tilelli Jr.]
-
A.
Daniel P. Higgins
Daniel P. Higgins was an architect associated with the design work on the Jefferson Memorial in Washington, D.C.
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B.
Patrick E. Haggerty
Patrick E. Haggerty was an American engineer and business executive who played a pivotal role in the early semiconductor industry and the growth of Texas Instruments into a major technology company.
-
C.
Thomas N. Margulis
Thomas N. Margulis is known primarily as the former husband of renowned evolutionary biologist Lynn Margulis.
-
D.
Daniel P. Hanley
Daniel P. Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
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E.
Thomas J. Biersteker
Thomas J. Biersteker is an American political scientist and international relations scholar known for his work on global governance, sanctions, and international security.
- 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: John H. Tilelli Jr. Target entity description: John H. Tilelli Jr. is a retired four-star U.S. Army general who served as Vice Chief of Staff of the Army and later commanded United States Forces Korea.
-
A.
Daniel P. Higgins
Daniel P. Higgins was an architect associated with the design work on the Jefferson Memorial in Washington, D.C.
-
B.
Patrick E. Haggerty
Patrick E. Haggerty was an American engineer and business executive who played a pivotal role in the early semiconductor industry and the growth of Texas Instruments into a major technology company.
-
C.
Thomas N. Margulis
Thomas N. Margulis is known primarily as the former husband of renowned evolutionary biologist Lynn Margulis.
-
D.
Daniel P. Hanley
Daniel P. Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
-
E.
Thomas J. Biersteker
Thomas J. Biersteker is an American political scientist and international relations scholar known for his work on global governance, sanctions, and international security.
- F. None of above. chosen
Statements (40)
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: John H. Tilelli Jr. Description of subject: John H. Tilelli Jr. is a retired four-star U.S. Army general who served as Vice Chief of Staff of the Army and later commanded United States Forces Korea.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.