Triple
T35752567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIA Formula One 25–18–15–12–10–8–6–4–2–1 scoring system |
E1033354
|
entity |
| Predicate | pointsPositionsCount |
P1029
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [FIA Formula One 25–18–15–12–10–8–6–4–2–1 scoring system, pointsPositionsCount, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsPositionsCount Context triple: [FIA Formula One 25–18–15–12–10–8–6–4–2–1 scoring system, pointsPositionsCount, 10]
-
A.
numberOfPositions
chosen
Indicates the total count of distinct positions or roles associated with a given entity.
-
B.
hasPositionsFor
Indicates that one entity offers or contains available roles, jobs, or positions for another entity.
-
C.
coordinatesPositionsIn
Indicates that one entity organizes or aligns the positions or placement of other entities within a specified context or space.
-
D.
polePositions
Indicates that one entity holds the pole position (starting first) relative to another entity in a competitive event, such as a race.
-
E.
hasNumberOfPoints
Indicates that an entity is associated with a specific count of points it possesses or comprises.
- 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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:06 p.m.