Triple
T30571648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabon national football team |
E778135
|
entity |
| Predicate | afconDebut |
P104087
|
FINISHED |
| Object | 1994 Africa Cup of Nations |
—
|
NE NERFINISHED |
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: 1994 Africa Cup of Nations | Statement: [Gabon national football team, afconDebut, 1994 Africa Cup of Nations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: afconDebut Context triple: [Gabon national football team, afconDebut, 1994 Africa Cup of Nations]
-
A.
afconParticipation
chosen
Indicates that an entity took part in, qualified for, or was involved as a competitor in the Africa Cup of Nations football tournament.
-
B.
afconQuarterFinalAppearances
Indicates the number of times an entity has reached the quarter-final stage of the Africa Cup of Nations tournament.
-
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.
ageAtWorldCupDebut
Indicates the age a person was when they first appeared in a World Cup match or tournament.
-
E.
madeWorldCupDebut
Indicates that an entity participated in their first-ever FIFA World Cup match or tournament in the specified year or event.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a16debc8190a12f5f65ced055d7 |
completed | May 2, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:22 p.m.