Triple
T33045169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1967 Formula One World Championship |
E845573
|
entity |
| Predicate | bestResultsCountedForDrivers |
P109348
|
FINISHED |
| Object | 5 best results from first 6 races |
—
|
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: 5 best results from first 6 races | Statement: [1967 Formula One World Championship, bestResultsCountedForDrivers, 5 best results from first 6 races]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestResultsCountedForDrivers Context triple: [1967 Formula One World Championship, bestResultsCountedForDrivers, 5 best results from first 6 races]
-
A.
bestResultsCounted
chosen
Indicates that the number of best or top-performing results in a given context has been determined and recorded.
-
B.
bestDriver
Indicates that the subject is considered the most skilled or highest-performing driver within a specified group or context.
-
C.
targetOutcomeForDrivers
Indicates the specific result or objective that an action, policy, or system is intended to achieve for drivers.
-
D.
featuresDrivers
Indicates that something includes or highlights specific drivers as notable components or participants.
-
E.
numberOfDriversPerTeam
Indicates the quantity of drivers associated with each team.
- 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_69f3495242e48190996a2cb2beab5455 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:24 a.m.