Triple
T26752674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairy World Taxi Spin |
E674583
|
entity |
| Predicate | hasRideVehiclesTheme |
P165157
|
FINISHED |
| Object | fairy taxis |
—
|
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: fairy taxis | Statement: [Fairy World Taxi Spin, hasRideVehiclesTheme, fairy taxis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRideVehiclesTheme Context triple: [Fairy World Taxi Spin, hasRideVehiclesTheme, fairy taxis]
-
A.
vehicleTheme
Indicates that an entity serves as the vehicle or means through which another entity, event, or action is carried out or expressed.
-
B.
vehicleNamesTheme
chosen
Indicates that the relationship or context involves a theme centered around vehicle names.
-
C.
hasIconicRide
Indicates that an entity is associated with a distinctive, well-known ride or attraction that it is famous for.
-
D.
hasAttractionTheme
Indicates that something (such as a place, event, or attraction) is characterized by or associated with a particular theme or motif.
-
E.
hasThemePark
Indicates that one entity owns, contains, or is associated with a theme park as part of its properties or offerings.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 27, 2026, 3:54 a.m.