Triple
T31755564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Nigel Channing |
E810547
|
entity |
| Predicate | roleInJourneyIntoImaginationWithFigment |
P128322
|
FINISHED |
| Object | tour guide through the Imagination Institute |
—
|
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: tour guide through the Imagination Institute | Statement: [Dr. Nigel Channing, roleInJourneyIntoImaginationWithFigment, tour guide through the Imagination Institute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInJourneyIntoImaginationWithFigment Context triple: [Dr. Nigel Channing, roleInJourneyIntoImaginationWithFigment, tour guide through the Imagination Institute]
-
A.
roleInThimbleweedPark
Indicates the specific role or function an entity has within the context of Thimbleweed Park.
-
B.
roleInDisney
chosen
Indicates that an entity has a role or participation in a Disney-related production, project, or organization.
-
C.
roleInMonstersInc
Indicates the specific function, position, or part an entity has within the context of the movie “Monsters, Inc.”
-
D.
roleInGoofTroop
Indicates the specific role or function an entity has within the context of the Goof Troop series or franchise.
-
E.
roleInTangled
Indicates that an entity has a specific role or function within the context of "Tangled" (e.g., the film, story, or related production).
- 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_69f348e340d48190b780fae618c51464 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ffe12ee59c8190bc7da386e6d5332d |
completed | May 10, 2026, 1:36 a.m. |
| PD | Predicate disambiguation | batch_69ffe0a138bc8190a3d4b48cd579e985 |
completed | May 10, 2026, 1:34 a.m. |
Created at: April 30, 2026, 11:29 p.m.