Triple
T20472081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The 33 |
E502217
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Robert Katz |
—
|
NE NERFINISHED |
How this triple was built (2 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: Robert Katz | Statement: [The 33, producer, Robert Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Katz Context triple: [The 33, producer, Robert Katz]
-
A.
Robert Katz
chosen
Robert Katz is a film producer best known for his work on projects such as the 1993 historical war drama "Gettysburg."
-
B.
Robert G. Katz
Robert G. Katz is a film producer known for his work on the movie "Idlewild."
-
C.
John R. Meyer
John R. Meyer was an American economist known for his influential work in transportation economics and quantitative economic history.
-
D.
Donald L. Kirkpatrick
Donald L. Kirkpatrick was an American professor and training expert best known for developing the influential four-level model for evaluating training programs.
-
E.
James G. March
James G. March was an influential organizational theorist and political scientist known for his work on decision-making, organizational behavior, and the "garbage can" model of organizational choice.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6996197908190b6570e2a7fd6cf67 |
completed | April 20, 2026, 9:23 p.m. |
Created at: April 16, 2026, 11:33 a.m.