Triple
T8933915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Leone national football team |
E212726
|
entity |
| Predicate | africaCupOfNationsDebut |
P33825
|
FINISHED |
| Object | 1994 |
—
|
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: 1994 | Statement: [Sierra Leone national football team, africaCupOfNationsDebut, 1994]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: africaCupOfNationsDebut Context triple: [Sierra Leone national football team, africaCupOfNationsDebut, 1994]
-
A.
wonAfricaCupOfNations
Indicates that the subject has won the Africa Cup of Nations football tournament.
-
B.
numberOfTitlesInAfricanCupOfChampionsClubs
Indicates the number of times an entity has won titles in the African Cup of Champions Clubs competition.
-
C.
WorldCupDebutYear
Indicates the year in which an entity (typically a team or player) first participated in a World Cup tournament.
-
D.
numberOfQualifiedTeamsFromAfrica
Indicates the count of teams from Africa that meet the specified qualification criteria.
-
E.
regionalCupFirstAppearance
chosen
Indicates the first time an entity participated in a specified regional cup competition.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc668fa87c8190bfeda820368b89e4 |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:57 p.m.