Triple
T34928142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghana national football team |
E1007348
|
entity |
| Predicate | afconWinningYears |
P41686
|
FINISHED |
| Object | 1963 |
—
|
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: 1963 | Statement: [Ghana national football team, afconWinningYears, 1963]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: afconWinningYears Context triple: [Ghana national football team, afconWinningYears, 1963]
-
A.
afconTitles
Indicates the number of Africa Cup of Nations (AFCON) championship titles an entity has won.
-
B.
afconTitleYear
chosen
Indicates the specific year in which a given Africa Cup of Nations (AFCON) title was won.
-
C.
afconRunnerUpYear
Indicates the year in which a given team or country finished as runner-up in the Africa Cup of Nations (AFCON) tournament.
-
D.
gulfCupWinningYears
Indicates the years in which an entity won the Gulf Cup tournament.
-
E.
afconParticipation
Indicates that an entity took part in, qualified for, or was involved as a competitor in the Africa Cup of Nations football tournament.
- 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_69f76dc3d83881909d5c3c14455cfa2c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.