Triple
T5696791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Amazing Adventures of Spider-Man |
E125558
|
entity |
| Predicate | numberOfRowsPerVehicle |
P23305
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [The Amazing Adventures of Spider-Man, numberOfRowsPerVehicle, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRowsPerVehicle Context triple: [The Amazing Adventures of Spider-Man, numberOfRowsPerVehicle, 3]
-
A.
rowsPerCar
chosen
Indicates the number of rows associated with or allocated to each individual car.
-
B.
numberOfRidersPerVehicle
Indicates the quantity of riders associated with each individual vehicle in the relationship.
-
C.
numberOfCarsPerUnit
Indicates the quantity of cars associated with each single unit of a specified measure (such as time, distance, or entity).
-
D.
ridersPerRow
Indicates the number of riders assigned or allowed to sit in each row.
-
E.
numberOfVehicles
Indicates the total count of vehicles associated with 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c0e0408190ab6c3cd3f907e80f |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.