Triple
T25745606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lincoln MKX |
E648336
|
entity |
| Predicate | introducedAsProductionModel |
P33675
|
FINISHED |
| Object | 2006 North American International Auto Show |
—
|
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: 2006 North American International Auto Show | Statement: [Lincoln MKX, introducedAsProductionModel, 2006 North American International Auto Show]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedAsProductionModel Context triple: [Lincoln MKX, introducedAsProductionModel, 2006 North American International Auto Show]
-
A.
introducedAsModel
chosen
Indicates that one entity is presented or identified to others in the role or capacity of a model.
-
B.
modelProduced
Indicates that a particular model has generated or produced a specified output, result, or artifact.
-
C.
introducedModelFamily
Indicates that an entity (such as a person or organization) is responsible for first presenting or launching a particular model family.
-
D.
firstModelIntroduced
Indicates that one entity is the earliest or original model introduced in relation to another entity or context.
-
E.
usesProductionModel
Indicates that one entity employs or relies on another entity as its primary or official production model in practice.
- 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 22, 2026, 3:51 a.m.