Triple
T21502849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Engelman |
E530522
|
entity |
| Predicate | roleInTheMask |
P144640
|
FINISHED |
| Object | 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: producer | Statement: [Robert Engelman, roleInTheMask, producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTheMask Context triple: [Robert Engelman, roleInTheMask, producer]
-
A.
roleInTheNightmareBeforeChristmas
Indicates the specific role or character that an entity has in the movie "The Nightmare Before Christmas."
-
B.
roleInWatchmen
Indicates that one entity has a specific role or function within the context of the work "Watchmen" in relation to the other entity.
-
C.
roleOfCharacter
Indicates that one entity serves as the narrative or functional role played by a character within a story, scenario, or context.
-
D.
roleInDishonored
Indicates that an entity holds or plays a particular role within the context of the work titled "Dishonored."
-
E.
isCostumedCharacterFor
Indicates that one entity serves as a costumed character representation or mascot for another entity, typically for promotional or entertainment purposes.
- 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.