Triple
T2904366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Gibbs Racing |
E62727
|
entity |
| Predicate | switchedToManufacturer |
P42640
|
FINISHED |
| Object | Toyota in 2008 |
—
|
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: Toyota in 2008 | Statement: [Joe Gibbs Racing, switchedToManufacturer, Toyota in 2008]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: switchedToManufacturer Context triple: [Joe Gibbs Racing, switchedToManufacturer, Toyota in 2008]
-
A.
manufacturerType
Indicates the classification or category of a manufacturer based on its role, characteristics, or production type.
-
B.
formerManufacturer
Indicates that an entity previously manufactured another entity but no longer does so.
-
C.
manufacturedBy
Indicates that an item or product is produced or created by a specific manufacturer or maker.
-
D.
manufacturerStatus
Indicates the current operational or business condition of a manufacturer in relation to the product or agreement in question.
-
E.
usedByManufacturer
Indicates that a manufacturer makes use of a particular resource, component, method, or tool in its production or operational processes.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0cd68d48190aea4afbdaed2d4bc |
completed | March 7, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69abdd19bac881908f047d616aca8438 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdd96670c8190b727f9ac27dadf67 |
completed | March 7, 2026, 8:11 a.m. |
Created at: March 6, 2026, 10:11 p.m.