Triple
T16260910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niki Lauda |
E394750
|
entity |
| Predicate | finalF1RetirementYear |
P120072
|
FINISHED |
| Object | 1985 |
—
|
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: 1985 | Statement: [Niki Lauda, finalF1RetirementYear, 1985]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: finalF1RetirementYear Context triple: [Niki Lauda, finalF1RetirementYear, 1985]
-
A.
f1CareerEndYear
Indicates the year in which an individual's professional career in a given field or role came to an end.
-
B.
activeInFormulaOneUntil
chosen
Indicates that an entity participated as an active competitor in Formula One up to and including a specified end time or season.
-
C.
F1ReturnYear
Indicates the year in which an entity’s F1 (Formula 1) participation or status returns or resumes.
-
D.
lastFormulaOneGrandPrixYear
Indicates the year in which the most recent Formula One Grand Prix involving the given entity took place.
-
E.
retiredFromRacing
Indicates that an entity has permanently stopped participating in competitive racing activities.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c3e5388190942b0237ab5d1f0f |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219f259e88190bf49d8408c04178e |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.