Triple
T8808713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford CD2 platform |
E209599
|
entity |
| Predicate | usedInModelYearRange |
P4161
|
FINISHED |
| Object | approximately 2001–2012 |
—
|
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: approximately 2001–2012 | Statement: [Ford CD2 platform, usedInModelYearRange, approximately 2001–2012]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInModelYearRange Context triple: [Ford CD2 platform, usedInModelYearRange, approximately 2001–2012]
-
A.
modelYears
chosen
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.
yearOfUse
Indicates the specific year during which something was in use or actively utilized.
-
C.
winnerModelYear
Indicates that a model was the winning model for a particular year.
-
D.
usedForSeasonRange
Indicates the span of seasons or time period during which something is intended or suitable to be used.
-
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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fd4cbec8190a929d4e60da8ad65 |
completed | March 31, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1f28ec8190a34311cb412920c2 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:45 p.m.