Triple
T26819423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tempesto |
E675204
|
entity |
| Predicate | riderCapacityPerTrain |
P24242
|
FINISHED |
| Object | 18 |
—
|
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: 18 | Statement: [Tempesto, riderCapacityPerTrain, 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riderCapacityPerTrain Context triple: [Tempesto, riderCapacityPerTrain, 18]
-
A.
vehiclesPerTrain
Indicates the number of vehicles that are attached to or make up a single train.
-
B.
transportCapacity
Indicates the maximum quantity of people, goods, or materials that can be transported by an entity or system within a given operation or time frame.
-
C.
numberOfRidersPerVehicle
chosen
Indicates the quantity of riders associated with each individual vehicle in the relationship.
-
D.
trainsPerSide
Indicates the number of trains allocated or operating on each side (e.g., direction, platform, or segment) within a system or configuration.
-
E.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
- 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_69eee9b6b28481909332f83eb17e5170 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61a886f148190b0de71e54e905958 |
completed | May 2, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 4:54 a.m.