Triple
T9536737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimbabwe national football team |
E230036
|
entity |
| Predicate | COSAFA CupTitleYear |
P88606
|
FINISHED |
| Object | 2000 |
—
|
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: 2000 | Statement: [Zimbabwe national football team, COSAFA CupTitleYear, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: COSAFA CupTitleYear Context triple: [Zimbabwe national football team, COSAFA CupTitleYear, 2000]
-
A.
wonAfricaCupOfNations
Indicates that the subject has won the Africa Cup of Nations football tournament.
-
B.
AfricaCupOfNationsRunnersUp
Indicates that the subject finished as the runner-up (second place) in an edition of the Africa Cup of Nations tournament.
-
C.
ConfederationsCupYear
Indicates the specific year in which a given FIFA Confederations Cup tournament took place.
-
D.
numberOfTitlesInAfricanCupOfChampionsClubs
Indicates the number of times an entity has won titles in the African Cup of Champions Clubs competition.
-
E.
afconTitleYear
Indicates the specific year in which a given Africa Cup of Nations (AFCON) title was won.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98ce884c8190a8b3c2dc7c73c2c9 |
completed | April 1, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69cca56c44f88190a54a5d2a133bb07e |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca89f1d748190bf3636bea28d8a37 |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 8:01 p.m.