Triple
T36108942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Formula One constructor |
E1044436
|
entity |
| Predicate | hasScoringRule |
P79635
|
FINISHED |
| Object | points awarded to top finishers per race |
—
|
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: points awarded to top finishers per race | Statement: [Formula One constructor, hasScoringRule, points awarded to top finishers per race]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScoringRule Context triple: [Formula One constructor, hasScoringRule, points awarded to top finishers per race]
-
A.
hasScorer
Indicates that one entity serves as the scorer (e.g., the one who scores points, goals, or evaluations) in relation to another entity.
-
B.
hasScoringUnit
Indicates that one entity possesses or is associated with a unit used for scoring, measurement, or point allocation in a given context.
-
C.
hasScoreSystem
chosen
Indicates that an entity uses, is governed by, or is associated with a particular scoring or rating system.
-
D.
hasScoreBy
Indicates that one entity possesses or is associated with a score that was assigned, produced, or determined by another entity.
-
E.
hasScoreType
Indicates that an entity is associated with a particular type or category of score.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
Created at: May 3, 2026, 4:08 p.m.