Triple
T5707790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Speed Train |
E125827
|
entity |
| Predicate | numberOfPowerCarsPerSet |
P53408
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [High Speed Train, numberOfPowerCarsPerSet, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPowerCarsPerSet Context triple: [High Speed Train, numberOfPowerCarsPerSet, 2]
-
A.
numberOfPowerCars
chosen
Indicates the relationship specifying how many power cars (self-propelled units) are associated with or contained in a given train or rail consist.
-
B.
numberOfCarsPerSet
Indicates the quantity of cars that are included within a single set.
-
C.
vehiclesPerTrain
Indicates the number of vehicles that are attached to or make up a single train.
-
D.
numberOfTrainsetsBuilt
Indicates the total count of trainsets that have been constructed or produced.
-
E.
numberOfPassengerCars
Indicates the total count of passenger cars associated with or contained in a given entity or context.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024892fd88190a91133fc88365410 |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.