Triple
T38335870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMW M340i |
E1037953
|
entity |
| Predicate | trimFeature |
P83851
|
FINISHED |
| Object | M-specific exterior styling |
—
|
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: M-specific exterior styling | Statement: [BMW M340i, trimFeature, M-specific exterior styling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trimFeature Context triple: [BMW M340i, trimFeature, M-specific exterior styling]
-
A.
trimFeatures
Indicates that certain features or attributes of an entity are reduced, removed, or cut down, typically to simplify or optimize it.
-
B.
trimCharacteristic
chosen
Indicates that one entity defines or specifies a trimming-related property or feature of another entity.
-
C.
trimName
Indicates that an entity’s name is shortened or cleaned by removing leading, trailing, or unnecessary characters.
-
D.
cutFrom
Indicates that one entity has been removed or separated from another entity by cutting.
-
E.
trimLevel
Indicates the specific configuration or package level of features or options applied to an item, typically distinguishing variants within the same base model.
- 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_69f76e20d65c81909619ac0dd85c56f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcc7a4d7f881908b43b960911b81e9 |
completed | May 7, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69fcc589720c819089c8f500fea3c86a |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.