Triple
T35040030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Setia Jaya KTM station via BRT |
E1011043
|
entity |
| Predicate | operatorRailComponent |
P203097
|
FINISHED |
| Object | Keretapi Tanah Melayu Berhad |
—
|
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: Keretapi Tanah Melayu Berhad | Statement: [Setia Jaya KTM station via BRT, operatorRailComponent, Keretapi Tanah Melayu Berhad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorRailComponent Context triple: [Setia Jaya KTM station via BRT, operatorRailComponent, Keretapi Tanah Melayu Berhad]
-
A.
railComponent
Indicates a relationship where one entity is a structural or functional part of a rail or railway system component of another entity.
-
B.
railwayInfrastructureManager
Indicates that one entity is responsible for managing, maintaining, and operating the railway infrastructure used by another entity.
-
C.
railInterface
Indicates a connection or interaction between entities via a rail-based system or interface.
-
D.
railOptions
Indicates the available rail-related choices or configurations that can be selected or applied in a given context.
-
E.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
- F. None of above. chosen
Provenance (4 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_6a011ee3507081908b42de4278ae0b83 |
completed | May 11, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_6a011e874420819091cac3f08e8aa3f9 |
completed | May 11, 2026, 12:10 a.m. |
| PDg | Predicate description generation | batch_6a011ee2a6408190b3b2763d01bac623 |
completed | May 11, 2026, 12:12 a.m. |
Created at: May 3, 2026, 4:01 p.m.