Triple
T27407751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kędzierzyn-Koźle |
E692052
|
entity |
| Predicate | hasNotableSportsClub |
P111529
|
FINISHED |
| Object | ZAKSA Kędzierzyn-Koźle |
—
|
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: ZAKSA Kędzierzyn-Koźle | Statement: [Kędzierzyn-Koźle, hasNotableSportsClub, ZAKSA Kędzierzyn-Koźle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSportsClub Context triple: [Kędzierzyn-Koźle, hasNotableSportsClub, ZAKSA Kędzierzyn-Koźle]
-
A.
hasSportsClubs
Indicates that an entity possesses, hosts, or is associated with one or more sports clubs.
-
B.
hasNotableSportAssociation
Indicates a relationship where an entity is significantly connected to, recognized for, or prominently involved with a particular sport or sports organization.
-
C.
notableClubsInclude
chosen
Indicates that the specified clubs are among the particularly significant or well-known clubs associated with the given entity.
-
D.
hasNotableClubGroup
Indicates that an entity is associated with a significant or distinguished club or group.
-
E.
notableClub
Indicates that an entity is prominently associated with or recognized for membership in 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_69ef5205fc808190ad3efc5525b8e6d6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69fe779248c081909f0ed1a2a0df23db |
completed | May 8, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69fe76eaf6d48190998bc7168749cc42 |
completed | May 8, 2026, 11:51 p.m. |
Created at: April 27, 2026, 12:31 p.m.