Triple
T25207326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clayton railway station |
E631287
|
entity |
| Predicate | hasPassengerSuburbCatchment |
P163825
|
FINISHED |
| Object | Clayton South |
—
|
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: Clayton South | Statement: [Clayton railway station, hasPassengerSuburbCatchment, Clayton South]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerSuburbCatchment Context triple: [Clayton railway station, hasPassengerSuburbCatchment, Clayton South]
-
A.
hasPassengerSuburbCatchment
chosen
Indicates that a passenger transport service draws or serves its users primarily from a particular suburban catchment area.
-
B.
containsSuburbs
Indicates that a larger geographic area or administrative region includes one or more suburbs within its boundaries.
-
C.
isOuterSuburbOf
Indicates that one place is a suburban area located on the outer edge or periphery of another, typically larger, urban area.
-
D.
hasSuburbAlong
Indicates that a larger area or route is associated with, or passes by, one or more suburbs located along its extent.
-
E.
hasNearbySuburb
Indicates that one location has another location as a suburb situated in close geographic proximity.
- 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_69e75a8b86c4819089eda22c843b739f |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 21, 2026, 12:52 p.m.