Triple
T26648737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodlands Checkpoint |
E668990
|
entity |
| Predicate | hasNearbyMRTStation |
P33877
|
FINISHED |
| Object | Woodlands MRT 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: Woodlands MRT station | Statement: [Woodlands Checkpoint, hasNearbyMRTStation, Woodlands MRT station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyMRTStation Context triple: [Woodlands Checkpoint, hasNearbyMRTStation, Woodlands MRT station]
-
A.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
B.
nearMetroStation
chosen
Indicates that one entity is located close to or within a short walking distance of a metro (subway) station.
-
C.
hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
-
D.
subwayServiceAtNearbyStation
Indicates that there is subway service available at a station located near the referenced place or entity.
-
E.
hasNearbyUndergroundStationEntrance
Indicates that one entity is located close to an entrance of an underground (subway/metro) 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_69ee9d00eb5481908d6c6d0ada2f0c9a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: April 27, 2026, 2:32 a.m.