Triple
T15689089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Horn |
E380277
|
entity |
| Predicate | availableEngines |
P17976
|
FINISHED |
| Object | various Ram 1500 gasoline engines depending on model year |
—
|
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: various Ram 1500 gasoline engines depending on model year | Statement: [Big Horn, availableEngines, various Ram 1500 gasoline engines depending on model year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: availableEngines Context triple: [Big Horn, availableEngines, various Ram 1500 gasoline engines depending on model year]
-
A.
offeredEngineType
chosen
Indicates that a particular type of engine is made available or provided as an option in a given context.
-
B.
historicallySuppliedEnginesFor
Indicates that one entity has, in the past, provided engines to another entity, typically as a supplier or manufacturer.
-
C.
engineName
Indicates the specific name assigned to an engine associated with an entity.
-
D.
numberOfEngines
Indicates the quantity of engines associated with or used by an entity.
-
E.
availableEngineDisplacement
Indicates the range or specific values of engine displacement that are offered or applicable for a given 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4cee5481908699fbb2b7bdd2f6 |
completed | April 16, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69deda8c856c8190882330114f9a1a5f |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:44 a.m.