Triple
T35752560
| 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 | pointsForFourthPlace |
P184898
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [FIA Formula One 25–18–15–12–10–8–6–4–2–1 scoring system, pointsForFourthPlace, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsForFourthPlace Context triple: [FIA Formula One 25–18–15–12–10–8–6–4–2–1 scoring system, pointsForFourthPlace, 12]
-
A.
fourthPlace
Indicates that an entity holds the fourth position or rank in an ordered sequence, competition, or hierarchy.
-
B.
pointsForThirdPlace
Indicates the number of points awarded to an entity for finishing in third place in a ranking or competition.
-
C.
fourthPlacePopularVoteShare
Indicates the proportion of total popular votes received by the candidate or option that finished in fourth place in an election or vote.
-
D.
fourthPlaceQualifiedFor
Indicates that the entity finishing in fourth place has earned qualification for a subsequent stage, event, or competition.
-
E.
westPointsFourthQuarter
Indicates that the referenced points were scored by the West team during the fourth quarter of a game.
- F. None of above. chosen
Provenance (4 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_69f7b628b17c8190aa058c1a51852a27 |
completed | May 3, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b5cadd308190a864245a21b08f9a |
completed | May 3, 2026, 8:53 p.m. |
Created at: May 3, 2026, 4:06 p.m.