Triple
T29447602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 6 Hours of Spa-Francorchamps |
E746891
|
entity |
| Predicate | hasMultipleDriverLineups |
P139469
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [6 Hours of Spa-Francorchamps, hasMultipleDriverLineups, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleDriverLineups Context triple: [6 Hours of Spa-Francorchamps, hasMultipleDriverLineups, yes]
-
A.
basedOnLineupsOf
Indicates that something is derived from, determined by, or constructed using specific lineups.
-
B.
hasRotatingLineup
chosen
Indicates that the composition of participants in a group or ensemble changes periodically rather than remaining fixed.
-
C.
numberOfDriversPerTeam
Indicates the quantity of drivers associated with each team.
-
D.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
E.
usesNumberOfPlayersOnFieldPerTeam
Indicates that the relationship specifies or depends on how many players each team has on the field at a given time.
- 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 28, 2026, 3:29 p.m.