Triple
T7210641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2003 Detroit Auto Show (as 2005 model) |
E149391
|
entity |
| Predicate | modelYearFocus |
P29328
|
FINISHED |
| Object | 2005 model year vehicles |
—
|
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: 2005 model year vehicles | Statement: [2003 Detroit Auto Show (as 2005 model), modelYearFocus, 2005 model year vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelYearFocus Context triple: [2003 Detroit Auto Show (as 2005 model), modelYearFocus, 2005 model year vehicles]
-
A.
modelYears
Indicates the association between a product (often a vehicle or device) and the specific calendar years in which that model version was produced or marketed.
-
B.
winnerModelYear
Indicates that a model was the winning model for a particular year.
-
C.
demonstrationYear
Indicates the year in which a demonstration, display, or public showing of something took place.
-
D.
yearOfManufacture
Indicates the specific calendar year in which an item was produced or manufactured.
-
E.
focusesOnYears
chosen
Indicates that something is primarily concerned with or directed toward specific years or time periods.
- 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_69c687eca814819095abb52316b1af80 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e96de4f081908f29b30c95e349f5 |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e75f84e481909e7866186ae80cff |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:53 p.m.