Triple
T646665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GMC |
E11255
|
entity |
| Predicate | notableModelLine |
P1503
|
FINISHED |
| Object | Sierra pickup line |
—
|
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: Sierra pickup line | Statement: [GMC, notableModelLine, Sierra pickup line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableModelLine Context triple: [GMC, notableModelLine, Sierra pickup line]
-
A.
notableModel
chosen
Indicates that an entity is a particularly important, influential, or exemplary instance or version within a broader category or system.
-
B.
notableEngineType
Indicates that an entity is particularly recognized for using or being associated with a specific type of engine.
-
C.
notableElectricVariant
Indicates that one entity is a notable or significant electric-powered version or variant of another entity.
-
D.
notableTie
Indicates a significant connection or association between entities that is noteworthy or distinguished in some context.
-
E.
notableEdition
Indicates that a particular edition or version of a work is especially significant or noteworthy in relation to that work.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f1b24b08190897d8aedb877bd83 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0c0dcc8190849211d45489a5a7 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.