Triple
T12243827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 17 (Roush Fenway Racing NASCAR car number) |
E291799
|
entity |
| Predicate | hasCarNumber |
P91439
|
FINISHED |
| Object | 17 |
—
|
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: 17 | Statement: [No. 17 (Roush Fenway Racing NASCAR car number), hasCarNumber, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarNumber Context triple: [No. 17 (Roush Fenway Racing NASCAR car number), hasCarNumber, 17]
-
A.
hasPlate
Indicates that one entity possesses, is equipped with, or includes a plate as part of its attributes or components.
-
B.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
C.
registrationNumber
Indicates the unique identifier assigned to an entity as part of an official or formal registration process.
-
D.
droveCarNumber
Indicates that a person operated or was driving a specific car identified by its number.
-
E.
notableVehicleNumber
chosen
Indicates that a specific vehicle is identified as notable or significant by a particular number or identifier.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91d38ee10819093ed41d2954bf4ef |
completed | April 10, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69d91c46dcd88190a263db30804bff36 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.