Triple
T1306071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Market Street retail area |
E27880
|
entity |
| Predicate | hasNearbyStop |
P15438
|
FINISHED |
| Object | Market Street tram stop |
—
|
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: Market Street tram stop | Statement: [Market Street retail area, hasNearbyStop, Market Street tram stop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyStop Context triple: [Market Street retail area, hasNearbyStop, Market Street tram stop]
-
A.
hasPublicTransportStop
chosen
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
-
B.
hasAdjacentBusStation
Indicates that one location has a bus station situated directly next to or very near it.
-
C.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
D.
hasBusStation
Indicates that a place or area contains or is served by a bus station.
-
E.
nearestPassengerRailStation
Indicates that one entity is the closest passenger rail station in distance to 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c15490a88190872c3d2698a8f9c9 |
completed | March 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69a4bee9e4a88190b22ab2ee831a23c9 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.