Triple
T29951797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurin & Klement racing team |
E760786
|
entity |
| Predicate | productTypeRaced |
P192646
|
FINISHED |
| Object | automobiles |
—
|
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: automobiles | Statement: [Laurin & Klement racing team, productTypeRaced, automobiles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productTypeRaced Context triple: [Laurin & Klement racing team, productTypeRaced, automobiles]
-
A.
racingModel
Indicates that one entity is a specific model or version designed or configured for racing in relation to another entity.
-
B.
raceComponent
Indicates that one entity is a constituent part, segment, or stage within a larger race or racing event involving another entity.
-
C.
vehicleRaced
Indicates that one vehicle participated in a race or competitive speed event against another vehicle.
-
D.
hasRacingSide
Indicates that an entity possesses or is associated with a side or aspect specifically dedicated to racing.
-
E.
raceCategory
Indicates the classification of an entity into a specific race or racial group within a defined categorization system.
- 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_69f2246562b881909d57622f4086d43d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
| PDg | Predicate description generation | batch_69fd231bdd108190900369e07c854e95 |
completed | May 7, 2026, 11:41 p.m. |
Created at: April 29, 2026, 6:26 p.m.