Triple
T25626352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baynards |
E642443
|
entity |
| Predicate | hasFormerTransportFacility |
P65217
|
FINISHED |
| Object | Baynards railway station |
—
|
NE NERFINISHED |
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: Baynards railway station | Statement: [Baynards, hasFormerTransportFacility, Baynards railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerTransportFacility Context triple: [Baynards, hasFormerTransportFacility, Baynards railway station]
-
A.
hasFormerStation
chosen
Indicates that an entity previously had a particular station (e.g., a stop, depot, or facility) that is no longer in active use or part of its current infrastructure.
-
B.
hasFormerAirport
Indicates that an entity previously had an airport that is no longer in operation or no longer exists.
-
C.
previousTransport
Indicates that one entity served as the immediately preceding mode or instance of transport for another entity in a sequence of movements or journeys.
-
D.
formerTransport
Indicates that an entity previously served as a means of transportation for another entity but no longer does so.
-
E.
hasFormerBuilding
Indicates that an entity previously occupied or used a different building, which is identified as its former building.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 21, 2026, 5:14 p.m.