Triple
T32233625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Circle Tour of Disneyland |
E823405
|
entity |
| Predicate | boardingStation |
P17223
|
FINISHED |
| Object | Main Street, U.S.A. Station |
—
|
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: Main Street, U.S.A. Station | Statement: [Grand Circle Tour of Disneyland, boardingStation, Main Street, U.S.A. Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boardingStation Context triple: [Grand Circle Tour of Disneyland, boardingStation, Main Street, U.S.A. Station]
-
A.
startingStation
chosen
Indicates the station or location where a journey, route, or trip begins.
-
B.
airportStation
Indicates a location functions as an airport facility where air transport operations occur.
-
C.
accessibleFromStation
Indicates that a location or facility can be reached directly or conveniently starting from a given station.
-
D.
hasBoardingAreaFor
Indicates that one entity provides or contains a designated area where passengers can board another entity (such as a vehicle or vessel).
-
E.
stationName
Indicates the name assigned to a particular station in the relationship.
- 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_69f3490c140481908ed53b98b561eaa1 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bbfcb370819088ba309249ce82f1 |
completed | May 3, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:39 a.m.