Triple
T12262386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milsons Point railway station |
E292255
|
entity |
| Predicate | distanceFromCentral |
P1299
|
FINISHED |
| Object | approximately 3.3 kilometres |
—
|
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: approximately 3.3 kilometres | Statement: [Milsons Point railway station, distanceFromCentral, approximately 3.3 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromCentral Context triple: [Milsons Point railway station, distanceFromCentral, approximately 3.3 kilometres]
-
A.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
B.
distanceFromCoreRegion
Indicates the spatial or conceptual distance between an entity and a defined core or central region.
-
C.
distanceFromMajorCity
Indicates the measured distance between a given location and a specified major city.
-
D.
distanceFromHamilton
Indicates the spatial distance between a given entity and the location identified as Hamilton.
-
E.
distanceFromGrandCentral
Indicates the spatial distance between a given entity and Grand Central.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.