Triple
T16830862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corporate Average Fuel Economy program |
E409143
|
entity |
| Predicate | implementedFromModelYear |
P94273
|
FINISHED |
| Object | 1978 |
—
|
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: 1978 | Statement: [Corporate Average Fuel Economy program, implementedFromModelYear, 1978]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: implementedFromModelYear Context triple: [Corporate Average Fuel Economy program, implementedFromModelYear, 1978]
-
A.
becameStandaloneModelYear
Indicates the year in which an entity first transitioned into being recognized or produced as an independent, standalone model.
-
B.
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.
-
C.
updatedSpecificationYear
Indicates the year in which the specification for an entity was last revised or updated.
-
D.
winnerModelYear
Indicates that a model was the winning model for a particular year.
-
E.
adoptedInstrumentYear
chosen
Indicates the year in which an instrument (such as a policy, law, or agreement) was formally adopted or put into effect.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b316acc881909c686add53d72388 |
completed | April 18, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:23 a.m.