Triple
T29620845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Die Wölfe |
E754989
|
entity |
| Predicate | associatedWithOwnerSponsor |
P35686
|
FINISHED |
| Object | Volkswagen |
E1148260
|
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: Volkswagen | Statement: [Die Wölfe, associatedWithOwnerSponsor, Volkswagen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithOwnerSponsor Context triple: [Die Wölfe, associatedWithOwnerSponsor, Volkswagen]
-
A.
sponsorAssociatedWith
Indicates a relationship where a sponsor is connected to, involved with, or responsible for supporting another entity.
-
B.
associatedWithSupporters
Indicates that an entity has a relationship or connection with individuals or groups who support or advocate for it.
-
C.
clubOwnerSponsor
Indicates that a sponsor provides financial or material support to a club that an owner is associated with or responsible for.
-
D.
hasSponsor
chosen
Indicates that one entity financially or otherwise supports another entity, typically in exchange for recognition or other benefits.
-
E.
associatedWithStand
Indicates a relationship where an entity is linked or connected to a particular stand, such as being located at, operating in, or otherwise related to that stand.
- 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_69f0ef86b6ec8190a87fff07fd983b1e |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2661549654819094c29a40b79e697c |
completed | June 8, 2026, 6:29 a.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 28, 2026, 6:34 p.m.