Triple
T21502877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Engelman |
E530522
|
entity |
| Predicate | roleInTheGoldenCompass |
P144652
|
FINISHED |
| Object | executive producer |
—
|
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: executive producer | Statement: [Robert Engelman, roleInTheGoldenCompass, executive producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTheGoldenCompass Context triple: [Robert Engelman, roleInTheGoldenCompass, executive producer]
-
A.
roleInTheBlackCauldron
Indicates that an entity has a specific role or appearance in the work "The Black Cauldron."
-
B.
roleInTheology
Indicates the specific function, position, or significance an entity holds within a theological system, doctrine, or belief framework.
-
C.
roleInLegendarium
Indicates that one entity serves a particular narrative or functional role within the fictional mythos or legendarium associated with another entity.
-
D.
roleInTheNightmareBeforeChristmas
Indicates the specific role or character that an entity has in the movie "The Nightmare Before Christmas."
-
E.
roleInHarryPotter
Indicates that one entity has a specific role or character part within the Harry Potter series in relation to the other entity.
- F. None of above. chosen
Provenance (4 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea5deb388190a89a1f94285b7e55 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e6386c5a4481909c37f7de7e9fc025 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 16, 2026, 6:24 p.m.