Triple
T6760380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feigl |
E154574
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Michael Feigl
Michael Feigl is an individual notable enough to be specifically cited as a bearer of the surname Feigl.
|
E628758
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Michael Feigl | Statement: [Feigl, hasNotableBearer, Michael Feigl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Feigl Context triple: [Feigl, hasNotableBearer, Michael Feigl]
-
A.
Peter Feigl
Peter Feigl is a former Austrian professional tennis player who competed on the international circuit in the 1970s and early 1980s.
-
B.
Ralph Rosenblum
Ralph Rosenblum was an American film editor best known for his influential work on landmark comedies and dramas, including several early Woody Allen films.
-
C.
Daniel Fuchs
Daniel Fuchs was an American novelist and screenwriter known for his Brooklyn-set fiction and acclaimed Hollywood screenplays, including several classic film noirs.
-
D.
Philip Steuer
Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
-
E.
Donald A. Wollheim
Donald A. Wollheim was an influential American science fiction editor, publisher, and author, best known for founding DAW Books and helping to shape modern science fiction and fantasy publishing.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Michael Feigl Triple: [Feigl, hasNotableBearer, Michael Feigl]
Generated description
Michael Feigl is an individual notable enough to be specifically cited as a bearer of the surname Feigl.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Feigl Target entity description: Michael Feigl is an individual notable enough to be specifically cited as a bearer of the surname Feigl.
-
A.
Peter Feigl
Peter Feigl is a former Austrian professional tennis player who competed on the international circuit in the 1970s and early 1980s.
-
B.
Ralph Rosenblum
Ralph Rosenblum was an American film editor best known for his influential work on landmark comedies and dramas, including several early Woody Allen films.
-
C.
Daniel Fuchs
Daniel Fuchs was an American novelist and screenwriter known for his Brooklyn-set fiction and acclaimed Hollywood screenplays, including several classic film noirs.
-
D.
Philip Steuer
Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
-
E.
Donald A. Wollheim
Donald A. Wollheim was an influential American science fiction editor, publisher, and author, best known for founding DAW Books and helping to shape modern science fiction and fantasy publishing.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d212c31881909dfe8ca9de69acf7 |
completed | March 27, 2026, 6:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7510b2ad88190a48ce74631d321e6 |
completed | March 28, 2026, 3:54 a.m. |
| NEDg | Description generation | batch_69c752065b808190bf95333afb42b730 |
completed | March 28, 2026, 3:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7528ddd1c8190964a072741315afe |
completed | March 28, 2026, 4:01 a.m. |
Created at: March 27, 2026, 2:12 p.m.