Triple
T26461894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuki Tsunoda |
E665659
|
entity |
| Predicate | racingLicence |
P19269
|
FINISHED |
| Object | FIA Super Licence |
—
|
NE NERFINISHED |
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: FIA Super Licence | Statement: [Yuki Tsunoda, racingLicence, FIA Super Licence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: racingLicence Context triple: [Yuki Tsunoda, racingLicence, FIA Super Licence]
-
A.
typeOfLicense
chosen
Indicates the specific kind or category of license associated with an entity.
-
B.
licenceAuthority
Indicates that one entity has the official power or jurisdiction to grant, issue, or regulate licences for another entity or activity.
-
C.
drivingRecord
Indicates the documented history of a person’s driving behavior, including past violations, accidents, and compliance with traffic laws.
-
D.
racingAchievement
Indicates that an entity has attained a notable result, record, or milestone in a competitive racing context.
-
E.
countryOfLicence
Indicates the country that has issued or granted a particular licence.
- 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_69ee883e812c8190a9b5a9cdb87fee5e |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f612956424819083b0e451342a5811 |
completed | May 2, 2026, 3:04 p.m. |
| PD | Predicate disambiguation | batch_69f602d5c8808190a1fdbebd6f0981e8 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 27, 2026, 12:13 a.m.