Triple
T28125430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toontown |
E710912
|
entity |
| Predicate | hasAttractionInspiredBy |
P91336
|
FINISHED |
| Object | Mickey's Toontown |
—
|
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: Mickey's Toontown | Statement: [Toontown, hasAttractionInspiredBy, Mickey's Toontown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAttractionInspiredBy Context triple: [Toontown, hasAttractionInspiredBy, Mickey's Toontown]
-
A.
hasAttractionBasedOn
Indicates that one entity feels an attraction toward another entity that is specifically grounded in a particular basis, criterion, or set of characteristics.
-
B.
isAttractionFor
Indicates that one entity serves as an attraction or point of interest specifically intended for another entity (such as a person, group, or audience).
-
C.
hasAttractionRepresentation
Indicates that one entity serves as a representation, depiction, or model of an attraction associated with another entity.
-
D.
inspiredRealWorldAttraction
chosen
Indicates that one entity served as the creative basis or model for a real-world attraction associated with the other entity.
-
E.
containsAttraction
Indicates that one entity includes or encompasses an attraction (such as a point of interest, feature, or draw) within its bounds or scope.
- 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_69ef9b73bd288190a21ae3d6aa14f386 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 9:19 p.m.