Triple
T20511796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LL8 |
E503582
|
entity |
| Predicate | usedInModelYearsApprox |
P4161
|
FINISHED |
| Object | 2002–2009 |
—
|
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: 2002–2009 | Statement: [LL8, usedInModelYearsApprox, 2002–2009]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInModelYearsApprox Context triple: [LL8, usedInModelYearsApprox, 2002–2009]
-
A.
yearOfUse
Indicates the specific year during which something was in use or actively utilized.
-
B.
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.
-
C.
yearDeliveredApprox
Indicates that the year an item or entity was delivered is known only approximately, rather than as an exact calendar year.
-
D.
lastAppearanceYear
Indicates the calendar year in which an entity made its most recent appearance.
-
E.
approximateDesignYear
Indicates the estimated or inferred year in which something was designed, rather than a precisely known design year.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dcb8f5c8190b0d4c09f3669a8ec |
completed | April 20, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:36 a.m.