Triple
T35040019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Setia Jaya KTM station via BRT |
E1011043
|
entity |
| Predicate | adjacentToBRTStation |
P15095
|
FINISHED |
| Object | Setia Jaya BRT 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: Setia Jaya BRT station | Statement: [Setia Jaya KTM station via BRT, adjacentToBRTStation, Setia Jaya BRT station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentToBRTStation Context triple: [Setia Jaya KTM station via BRT, adjacentToBRTStation, Setia Jaya BRT station]
-
A.
hasAdjacentBusStation
chosen
Indicates that one location has a bus station situated directly next to or very near it.
-
B.
nearMetroStation
Indicates that one entity is located close to or within a short walking distance of a metro (subway) station.
-
C.
adjacentToStation
Indicates that one entity is located next to or immediately beside a station.
-
D.
hasPublicTransportStop
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
-
E.
nearCommuterRailStation
Indicates that one entity is located close to, or within a short walking distance of, a commuter 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_69f76dcea02c81908542a223f6d5059f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: May 3, 2026, 4:01 p.m.