Triple
T36115176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota Sports 800 |
E1044598
|
entity |
| Predicate | isFirstMassProducedSportsCarOf |
P35143
|
FINISHED |
| Object | Toyota |
—
|
NE NERFINISHED |
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: Toyota | Statement: [Toyota Sports 800, isFirstMassProducedSportsCarOf, Toyota]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFirstMassProducedSportsCarOf Context triple: [Toyota Sports 800, isFirstMassProducedSportsCarOf, Toyota]
-
A.
firstMassProductionBy
chosen
Indicates that the subject is the first entity to mass-produce the object or technology referenced.
-
B.
firstModelIntroduced
Indicates that one entity is the earliest or original model introduced in relation to another entity or context.
-
C.
championshipWinningCar
Indicates that a car is the specific vehicle that won a particular championship.
-
D.
firstMassProductionProductName
Indicates the name of the product that was the first to be mass-produced by a given entity.
-
E.
wasFirstProducedBy
Indicates that something (such as a product, work, or item) was initially created, manufactured, or brought into existence by a particular agent, organization, or producer.
- 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_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.