Triple
T6372349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NASCAR Technical Institute |
E143379
|
entity |
| Predicate | hasTrainingFacilityType |
P2836
|
FINISHED |
| Object | hands-on labs |
—
|
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: hands-on labs | Statement: [NASCAR Technical Institute, hasTrainingFacilityType, hands-on labs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingFacilityType Context triple: [NASCAR Technical Institute, hasTrainingFacilityType, hands-on labs]
-
A.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
B.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
C.
hasTrainingComplex
Indicates that an entity possesses or is associated with a dedicated facility or complex used for training activities.
-
D.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
E.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06829d76c819092b476631459233a |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ee055081908c79a1d151bd74cd |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:33 p.m.