Triple
T35447412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Master of Ceremonies |
E1024523
|
entity |
| Predicate | relatedWorkAuthorOccupation |
P196156
|
FINISHED |
| Object | political theorist |
—
|
LITERAL FINISHED |
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: political theorist | Statement: [the Master of Ceremonies, relatedWorkAuthorOccupation, political theorist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedWorkAuthorOccupation Context triple: [the Master of Ceremonies, relatedWorkAuthorOccupation, political theorist]
-
A.
relatedWorkCreatorOccupation
Indicates that the occupation specified is the professional role or job held by the creator of a related work.
-
B.
coAuthorOccupation
Indicates that two or more co-authors share the same or closely related professional occupation.
-
C.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
-
D.
hasAuthorOccupationOfAuthor
Indicates that an author has a specific occupation or professional role.
-
E.
hasOriginalWorkAuthorOccupation
chosen
Indicates that the occupation specified is the professional role held by the author of the original work on which the related entity is based.
- F. None of above.
Provenance (3 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_69f76df8089481909f0018266ee881b7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:04 p.m.