Triple
T7876965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CAF Women’s Champions League |
E182879
|
entity |
| Predicate | confederationCupFor |
P79523
|
FINISHED |
| Object | women’s club teams in Africa |
—
|
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: women’s club teams in Africa | Statement: [CAF Women’s Champions League, confederationCupFor, women’s club teams in Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: confederationCupFor Context triple: [CAF Women’s Champions League, confederationCupFor, women’s club teams in Africa]
-
A.
confederationCupQualifier
Indicates that an entity has qualified for participation in a Confederations Cup tournament.
-
B.
fifaConfederation
Indicates the regional football governing confederation with which an entity (typically a national team or association) is officially affiliated.
-
C.
wonConfederationsCup
Indicates that the subject has won the FIFA Confederations Cup tournament.
-
D.
ConfederationsCupTitles
Indicates the number of FIFA Confederations Cup championships an entity has won.
-
E.
ConfederationsCupAppearances
Indicates the number of times an entity has participated in the FIFA Confederations 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39bc07208190aa452cef8ca5b0d6 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf786ec748190b6347b0c94335550 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:57 p.m.