Triple
T14367440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hornsby railway station |
E356270
|
entity |
| Predicate | hasTrainStablingYard |
P18851
|
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: [Hornsby railway station, hasTrainStablingYard, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainStablingYard Context triple: [Hornsby railway station, hasTrainStablingYard, yes]
-
A.
hasRailYard
chosen
Indicates that one entity possesses, contains, or includes a rail yard as part of its facilities or infrastructure.
-
B.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
C.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
D.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
E.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8faf00e8819087d7100e9d8c1877 |
completed | April 14, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:15 a.m.