Triple
T37416112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyberjaya Utara MRT station |
E929713
|
entity |
| Predicate | publicTransportOperatorBrand |
P142506
|
FINISHED |
| Object | Rapid KL |
—
|
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: Rapid KL | Statement: [Cyberjaya Utara MRT station, publicTransportOperatorBrand, Rapid KL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicTransportOperatorBrand Context triple: [Cyberjaya Utara MRT station, publicTransportOperatorBrand, Rapid KL]
-
A.
publicTransportBrand
chosen
Indicates that a public transport service, line, or vehicle operates under or is associated with a specific brand or branding entity.
-
B.
publicTransportOperatorFor
Indicates that one entity operates or manages public transportation services for another entity or area.
-
C.
commuterRailBrand
Indicates that a commuter rail service operates under or is associated with a specific brand or branding identity.
-
D.
transportOperator
Indicates that an entity is responsible for operating or managing the transportation of people or goods between locations.
-
E.
notableTrainBrand
Indicates that an entity is a well-known or significant brand associated with trains or railway services.
- 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_69f76ebde49481908566cd96b37ccc84 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffe6e2eb688190a45fd2c6415cd86a |
completed | May 10, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69ffe65939488190a35b9c2e9c7ad868 |
completed | May 10, 2026, 1:58 a.m. |
Created at: May 3, 2026, 4:16 p.m.