Triple
T16350441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palembang LRT |
E397047
|
entity |
| Predicate | hasNumberOfTrainsets |
P50983
|
FINISHED |
| Object | 8 |
—
|
LITERAL FINISHED |
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: 8 | Statement: [Palembang LRT, hasNumberOfTrainsets, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfTrainsets Context triple: [Palembang LRT, hasNumberOfTrainsets, 8]
-
A.
numberOfTrainsetsBuilt
chosen
Indicates the total count of trainsets that have been constructed or produced.
-
B.
maintainsTrainsFor
Indicates that one entity is responsible for servicing, repairing, or otherwise keeping trains operational for another entity.
-
C.
trainCount
Indicates the number of trains associated with a given entity, context, or time period.
-
D.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
-
E.
vehiclesPerTrain
Indicates the number of vehicles that are attached to or make up a single train.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2facb37d0819093fe45446f1e79c1 |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.