Triple
T21690371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 125th Street station (Lexington Avenue Line) |
E535344
|
entity |
| Predicate | isLocalStopFor |
P144940
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [125th Street station (Lexington Avenue Line), isLocalStopFor, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLocalStopFor Context triple: [125th Street station (Lexington Avenue Line), isLocalStopFor, 6]
-
A.
isPassengerStop
Indicates that a location serves as a designated place where passengers may board or alight from a vehicle or transport service.
-
B.
hasStopNear
Indicates that one entity has a stop or stopping point located in close proximity to another entity.
-
C.
hasStopArea
Indicates that an entity is associated with or contains a specific stop area, such as a designated location where vehicles stop.
-
D.
isLocalStationFor
Indicates that a station serves a specific local area or locality as its primary service point.
-
E.
hasStopType
Indicates that a stop or stopping point is classified as having a particular type or category of stop.
- F. None of above. chosen
Provenance (4 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_69e0c46a6ee481908836e1420fb78c9b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96ce2ff88190a6cbfff45bb6a04f |
completed | April 27, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69e6969113cc8190ab69855ef5667e4b |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:44 p.m.