Triple
T28807766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comfortline |
E727425
|
entity |
| Predicate | associatedModelCode |
P97305
|
FINISHED |
| Object | B7 Passat |
E38524
|
NE 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: B7 Passat | Statement: [Comfortline, associatedModelCode, B7 Passat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedModelCode Context triple: [Comfortline, associatedModelCode, B7 Passat]
-
A.
associatedWithModel
chosen
Indicates that one entity has a defined connection, linkage, or relationship with a particular model.
-
B.
associatedModelGeneration
Indicates that one entity is responsible for creating, producing, or generating another related model or representation.
-
C.
associatedWithMode
Indicates a relationship in which something is linked or connected to a particular mode, method, or manner of operation or behavior.
-
D.
linkedModel
Indicates that one model is associated or connected to another model, typically to reference or reuse its structure or behavior.
-
E.
relatedCode
Indicates that one code is associated with, linked to, or otherwise contextually connected to another code.
- F. None of above.
Provenance (4 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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_6a01d48f41f4819093a5b47288a073c1 |
completed | May 11, 2026, 1:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a25699720e4819097c9023ba6abed9c |
completed | June 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_6a01d3fa278c8190838174dd96ef5dde |
completed | May 11, 2026, 1:04 p.m. |
Created at: April 28, 2026, 6:29 a.m.