Triple
T7754243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swan Hill railway station |
E175847
|
entity |
| Predicate | hasNearbyBusStop |
P15438
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Swan Hill railway station, hasNearbyBusStop, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyBusStop Context triple: [Swan Hill railway station, hasNearbyBusStop, yes]
-
A.
hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
-
B.
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.
-
C.
hasStopNear
Indicates that one entity has a stop or stopping point located in close proximity to another entity.
-
D.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
E.
hasAdjacentBusStation
Indicates that one location has a bus station situated directly next to or very near it.
- 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_69c6996180088190832e38e8d83ff54a |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c705257ca08190a78c592a1e616da8 |
completed | March 27, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69c7016df2b08190b2330a2010691431 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:08 p.m.