Triple
T21721524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevrolet Bel Air (separate series) |
E536166
|
entity |
| Predicate | firstModelYearAsSeparateSeries |
P72840
|
FINISHED |
| Object | 1953 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: 1953 model year | Statement: [Chevrolet Bel Air (separate series), firstModelYearAsSeparateSeries, 1953 model year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstModelYearAsSeparateSeries Context triple: [Chevrolet Bel Air (separate series), firstModelYearAsSeparateSeries, 1953 model year]
-
A.
becameStandaloneModelYear
chosen
Indicates the year in which an entity first transitioned into being recognized or produced as an independent, standalone model.
-
B.
firstModelYearSales
Indicates the sales figures associated with the first model year of a product or item.
-
C.
yearModelTDevelopmentBegan
Indicates the calendar year in which the development of model T was initiated.
-
D.
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.
-
E.
hasModelSeries
Indicates a relationship where an item or product is associated with a specific model series it belongs to.
- 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efd96f1fbc8190a202f834aec1a319 |
completed | April 27, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:47 p.m.