Triple
T7031738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basketball Africa League |
E163285
|
entity |
| Predicate | usesNBAResources |
P74564
|
FINISHED |
| Object | NBA officiating and operations support |
—
|
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: NBA officiating and operations support | Statement: [Basketball Africa League, usesNBAResources, NBA officiating and operations support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNBAResources Context triple: [Basketball Africa League, usesNBAResources, NBA officiating and operations support]
-
A.
supportsBandwidths
Indicates that an entity is compatible with or can operate using the specified range or set of bandwidth values.
-
B.
hasNavigationUse
Indicates that something is used for navigation or serves a navigational function in relation to another entity.
-
C.
usesDRS
Indicates that one entity employs or relies on a specific Decision Review System (DRS) for evaluation, verification, or decision-making purposes.
-
D.
usesIP
Indicates that one entity makes use of, operates through, or is associated with a particular IP address.
-
E.
supportsNetworkingModel
Indicates that one entity provides compatibility with, or implementation of, a specified networking model for another entity.
- 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_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b9a2488190aea351d96afa5a12 |
completed | March 27, 2026, 7:59 p.m. |
| PDg | Predicate description generation | batch_69c6e456e89481908df42a1b4232a4a0 |
completed | March 27, 2026, 8:11 p.m. |
Created at: March 27, 2026, 2:36 p.m.