Triple
T12150191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigeria under-23 national football team |
E289431
|
entity |
| Predicate | allAfricaGamesSilverMedal |
P103220
|
FINISHED |
| Object | 2003 All-Africa Games |
—
|
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: 2003 All-Africa Games | Statement: [Nigeria under-23 national football team, allAfricaGamesSilverMedal, 2003 All-Africa Games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allAfricaGamesSilverMedal Context triple: [Nigeria under-23 national football team, allAfricaGamesSilverMedal, 2003 All-Africa Games]
-
A.
worldChampionshipSilverMedals
Indicates that the subject has won one or more silver medals at a world championship competition.
-
B.
olympicSilverMedals
Indicates that the subject has won one or more silver medals at the Olympic Games.
-
C.
EuropeanChampionshipSilverMedals
Indicates that the subject has won a silver medal in a European Championship competition.
-
D.
AsianGamesGoldMedals
Indicates that the subject has won one or more gold medals at the Asian Games.
-
E.
WorldCupMedal
Indicates that an entity has received a medal (e.g., gold, silver, bronze) for its performance in a FIFA World Cup tournament.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d915d58ab881908b5b7901990308a4 |
completed | April 10, 2026, 3:23 p.m. |
Created at: April 8, 2026, 9:49 p.m.