Triple
T9408687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bellas Artes metro station |
E226650
|
entity |
| Predicate | isMajorStop |
P29762
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bellas Artes metro station, isMajorStop, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMajorStop Context triple: [Bellas Artes metro station, isMajorStop, true]
-
A.
isMajorStationOn
Indicates that a station serves as a primary or significant stop on a particular route or line.
-
B.
majorStop
chosen
Indicates that a location functions as a primary or significant stop along a route or service path, typically where vehicles regularly halt for boarding, alighting, or key operations.
-
C.
isMajor
Indicates that an entity holds primary or greater significance, importance, or rank relative to others in a given context.
-
D.
isMajorInterchangeFor
Indicates that one location functions as a primary hub where multiple routes or lines connect or transfer between each other for another location.
-
E.
isMajorSeeWithin
Indicates that one entity is the primary or most significant location or area encompassed within the boundaries of another entity.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd52547f0c81908ed4f53b9f05ebaa |
completed | April 1, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:47 p.m.