Triple
T7205853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sokol Kiev |
E148662
|
entity |
| Predicate | languageOfLocalFanbase |
P11430
|
FINISHED |
| Object | Ukrainian |
—
|
LITERAL 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: Ukrainian | Statement: [Sokol Kiev, languageOfLocalFanbase, Ukrainian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLocalFanbase Context triple: [Sokol Kiev, languageOfLocalFanbase, Ukrainian]
-
A.
languageOfFanbase
Indicates the primary language or languages commonly used by a fanbase in its communication and expression.
-
B.
majorityLanguageOf
chosen
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
C.
hasFanBasePrimarilyIn
Indicates that an entity’s main or largest group of supporters, followers, or fans is located in a specified place or region.
-
D.
languageOfClubMedia
Indicates the language in which a club’s media or communications are produced or presented.
-
E.
languageOfCompetition
Indicates the language in which a competition is conducted or officially presented.
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e94ef5cc81908c33adcedf5c5054 |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:52 p.m.