Triple
T36844924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schinkel, Osnabrück |
E910516
|
entity |
| Predicate | hasAssociationWithSportsClub |
P36408
|
FINISHED |
| Object | VfL Osnabrück |
—
|
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: VfL Osnabrück | Statement: [Schinkel, Osnabrück, hasAssociationWithSportsClub, VfL Osnabrück]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociationWithSportsClub Context triple: [Schinkel, Osnabrück, hasAssociationWithSportsClub, VfL Osnabrück]
-
A.
associatedClubSport
Indicates that there is a relationship between a club and the sport with which it is connected or aligned.
-
B.
associatedClub2
Indicates that an entity has a secondary or additional affiliation or membership with a particular club.
-
C.
hasClub
Indicates that an entity is associated with or belongs to a particular club.
-
D.
associatedWithFootballClub
chosen
Indicates that there is a relationship of affiliation or connection between an entity and a football club.
-
E.
associatedClub1
Indicates that an entity has a primary or first-listed association with a particular club or organization.
- 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_69f76e7f65a881908651b702da592b6d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: May 3, 2026, 4:13 p.m.