Triple
T35758114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercedes-Benz W140 |
E1033499
|
entity |
| Predicate | coupéDesignation |
P32674
|
FINISHED |
| Object | C140 |
—
|
NE NERFINISHED |
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: C140 | Statement: [Mercedes-Benz W140, coupéDesignation, C140]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coupéDesignation Context triple: [Mercedes-Benz W140, coupéDesignation, C140]
-
A.
coupeIntroductionYear
Indicates the year in which a coupe model was first introduced.
-
B.
hasFullCarDesignation
Indicates that an entity is associated with a complete, formal car designation (such as full model name or code) rather than a partial or abbreviated identifier.
-
C.
headEndCarDesignation
Indicates the designation or identifier assigned to the car positioned at the head end of a train.
-
D.
racingModel
Indicates that one entity is a specific model or version designed or configured for racing in relation to another entity.
-
E.
carModel
chosen
Indicates the specific model designation of a car within a particular make or brand.
- 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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a1c138848190bdd27868794efd0f |
completed | May 3, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.