Triple
T14947209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigeria national basketball team |
E372696
|
entity |
| Predicate | AfroBasketTitles |
P94459
|
FINISHED |
| Object | 2015 AfroBasket |
—
|
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: 2015 AfroBasket | Statement: [Nigeria national basketball team, AfroBasketTitles, 2015 AfroBasket]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AfroBasketTitles Context triple: [Nigeria national basketball team, AfroBasketTitles, 2015 AfroBasket]
-
A.
afroBasketTitles
Indicates the number of AfroBasket championship titles a team or entity has won.
-
B.
afroBasketTitle
chosen
Indicates that a team or individual has won the AfroBasket basketball championship title.
-
C.
euroBasketTitles
Indicates the number of EuroBasket championship titles an entity (typically a national basketball team) has won.
-
D.
fibaWorldCupTitles
Indicates the number of FIBA Basketball World Cup championships an entity has won.
-
E.
EuroBasketMedal
Indicates that a team or player has won a medal (gold, silver, or bronze) in a EuroBasket basketball championship.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68e35c481908e47cd68441c5115 |
completed | April 15, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:39 a.m.