Triple
T3102720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMW 3 Series |
E64756
|
entity |
| Predicate | isOneOfManufacturerBestSellingModels |
P45322
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [BMW 3 Series, isOneOfManufacturerBestSellingModels, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfManufacturerBestSellingModels Context triple: [BMW 3 Series, isOneOfManufacturerBestSellingModels, true]
-
A.
isOneOfBestSellingCars
chosen
Indicates that the car is among the top-selling cars within a specified market or time period.
-
B.
hasModelSeries
Indicates a relationship where an item or product is associated with a specific model series it belongs to.
-
C.
lastModelProduced
Indicates that one entity is the most recently created or generated model associated with another entity.
-
D.
carModel
Indicates the specific model designation of a car within a particular make or brand.
-
E.
hasFranchiseModel
Indicates that one entity operates under, offers, or is associated with a business franchise system or structure defined by another entity.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada26df128819086541db7680c8c24 |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df06ed88190809f0683122caa5a |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:03 p.m.