Triple
T35254074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMW E10 |
E1018176
|
entity |
| Predicate | usedForModelSeries |
P39689
|
FINISHED |
| Object | BMW 02 Series |
—
|
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: BMW 02 Series | Statement: [BMW E10, usedForModelSeries, BMW 02 Series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForModelSeries Context triple: [BMW E10, usedForModelSeries, BMW 02 Series]
-
A.
usedInSeries
Indicates that something (such as an element, component, or concept) is employed or appears within a particular series.
-
B.
usedByModel
Indicates that something (such as a resource, method, or component) is utilized or consumed by a particular model.
-
C.
useOfModel
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
-
D.
usedToModel
Indicates that one entity serves as a model or representation for another entity, typically for purposes of analysis, simulation, or understanding.
-
E.
hasModelSeries
chosen
Indicates a relationship where an item or product is associated with a specific model series it belongs to.
- 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_69f76de407d081909dfc3c419817ae93 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: May 3, 2026, 4:02 p.m.