Triple
T9234871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercedes-Benz GLS |
E221910
|
entity |
| Predicate | firstModelYearAsGLS |
P72840
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Mercedes-Benz GLS, firstModelYearAsGLS, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstModelYearAsGLS Context triple: [Mercedes-Benz GLS, firstModelYearAsGLS, 2016]
-
A.
becameStandaloneModelYear
chosen
Indicates the year in which an entity first transitioned into being recognized or produced as an independent, standalone model.
-
B.
demonstrationYear
Indicates the year in which a demonstration, display, or public showing of something took place.
-
C.
yearModelTDevelopmentBegan
Indicates the calendar year in which the development of model T was initiated.
-
D.
firstModelYearSales
Indicates the sales figures associated with the first model year of a product or item.
-
E.
yearFirstDelivered
Indicates the calendar year in which something (such as a product, service, or item) was first delivered or made available.
- 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_69ca83ed628c8190bc02d641e57f097f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccee1cca0c8190bf587f54236c9e45 |
completed | April 1, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4765648190aa9445c4a22dc471 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:29 p.m.