Michael Thiel
E572103
Michael Thiel is an individual notable enough to be specifically distinguished from others sharing the surname Thiel.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Michael Thiel canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6091296 — 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: Michael Thiel Context triple: [Thiel, hasNotableBearer, Michael Thiel]
-
A.
Carl Thiel
Carl Thiel is a film and television composer known for his work on genre projects including the series adaptation of "From Dusk Till Dawn."
-
B.
Kevin Riepl
Kevin Riepl is an American composer best known for his atmospheric scores for films and video games, including work on titles like Gears of War and various horror and sci-fi projects.
-
C.
Michael Hainisch
Michael Hainisch was an Austrian politician and statesman who served as the first democratically elected President of Austria in the early 20th century.
-
D.
Michael Schroeder
Michael Schroeder is a software developer best known for his work on the GNU Screen terminal multiplexer.
-
E.
Erik Heinrichs
Erik Heinrichs was a Finnish general and senior military leader who played a key role in directing Finland’s armed forces during World War II.
- 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: Michael Thiel Target entity description: Michael Thiel is an individual notable enough to be specifically distinguished from others sharing the surname Thiel.
-
A.
Carl Thiel
Carl Thiel is a film and television composer known for his work on genre projects including the series adaptation of "From Dusk Till Dawn."
-
B.
Kevin Riepl
Kevin Riepl is an American composer best known for his atmospheric scores for films and video games, including work on titles like Gears of War and various horror and sci-fi projects.
-
C.
Michael Hainisch
Michael Hainisch was an Austrian politician and statesman who served as the first democratically elected President of Austria in the early 20th century.
-
D.
Michael Schroeder
Michael Schroeder is a software developer best known for his work on the GNU Screen terminal multiplexer.
-
E.
Erik Heinrichs
Erik Heinrichs was a Finnish general and senior military leader who played a key role in directing Finland’s armed forces during World War II.
- F. None of above. chosen
Statements (4)
| Predicate | Object |
|---|---|
| instanceOf |
given name and surname combination
ⓘ
human ⓘ |
| hasFamilyName | Thiel NERFINISHED ⓘ |
| hasGivenName | Michael NERFINISHED ⓘ |
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: Michael Thiel Description of subject: Michael Thiel is an individual notable enough to be specifically distinguished from others sharing the surname Thiel.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.