Triple
T9419385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huddersfield bus station |
E227111
|
entity |
| Predicate | hasBusStandCount |
P46981
|
FINISHED |
| Object | 30+ |
—
|
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: 30+ | Statement: [Huddersfield bus station, hasBusStandCount, 30+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusStandCount Context triple: [Huddersfield bus station, hasBusStandCount, 30+]
-
A.
hasBusStation
Indicates that a place or area contains or is served by a bus station.
-
B.
hasBusPlatforms
chosen
Indicates that a location or facility is equipped with one or more designated platforms for boarding or alighting from buses.
-
C.
hasTaxiStand
Indicates that a location or facility includes or is served by a designated taxi stand area where taxis can wait for passengers.
-
D.
isMainBusStationFor
Indicates that one bus station serves as the primary or central station for a particular area, network, or service.
-
E.
numberOfStandingPlaces
Indicates the total count of standing-only positions or spots available in a given context (e.g., a vehicle, venue, or area).
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd6c23c65081908d1009c26be66533 |
completed | April 1, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:48 p.m.