Triple
T8517952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BC Dnipro |
E201621
|
entity |
| Predicate | usesStandardBasketballCourt |
P83083
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [BC Dnipro, usesStandardBasketballCourt, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesStandardBasketballCourt Context triple: [BC Dnipro, usesStandardBasketballCourt, yes]
-
A.
capacityForBasketball
Indicates the ability or suitability of an entity to play or perform well in basketball.
-
B.
hasBallcourt
Indicates that a place, structure, or site includes or is equipped with a ballcourt as one of its features.
-
C.
hasBasketballLevel
Indicates that an entity possesses a specified level of skill, proficiency, or ranking in basketball.
-
D.
usesAmericanRules
Indicates that the action, process, or system is conducted according to American rules or standards rather than other rule sets.
-
E.
representsInBasketball
Indicates that one entity serves as an official representative (such as an agent, delegate, or spokesperson) for another entity specifically in the context of basketball.
- F. None of above. chosen
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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe626787c819087e72dd76b2d9310 |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30d453481908f897ed2b06e7534 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:15 p.m.