Triple
T11877339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Motor Trend Car of the Year 1966 |
E282561
|
entity |
| Predicate | awardedToModelYear |
P54787
|
FINISHED |
| Object | 1966 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: 1966 model year | Statement: [Motor Trend Car of the Year 1966, awardedToModelYear, 1966 model year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardedToModelYear Context triple: [Motor Trend Car of the Year 1966, awardedToModelYear, 1966 model year]
-
A.
winnerModelYear
chosen
Indicates that a model was the winning model for a particular year.
-
B.
CarOfTheYearIs
Indicates that a particular car has been designated as the "Car of the Year" for a given award, region, or time period.
-
C.
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.
-
D.
suspensionYear
Indicates the year in which a suspension (such as a ban, halt, or temporary discontinuation of activity) takes effect or is recorded.
-
E.
demonstrationYear
Indicates the year in which a demonstration, display, or public showing of something took place.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.