Triple
T21629809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amakhosi |
E533798
|
entity |
| Predicate | hasClubReputation |
P80732
|
FINISHED |
| Object | one of the most successful football clubs in South 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: one of the most successful football clubs in South Africa | Statement: [Amakhosi, hasClubReputation, one of the most successful football clubs in South Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClubReputation Context triple: [Amakhosi, hasClubReputation, one of the most successful football clubs in South Africa]
-
A.
haveReputation
Indicates that an entity is recognized or regarded in a certain way by others, reflecting its perceived character, quality, or status.
-
B.
clubReputation
chosen
Indicates the perceived status, prestige, or standing of a club within its relevant community or domain.
-
C.
hasQuirkyReputation
Indicates that an entity is regarded by others as having an unusual, eccentric, or unconventional character or style.
-
D.
hasReputationAmong
Indicates that an entity is regarded or perceived in a particular way by a specified group or audience.
-
E.
hasClub
Indicates that an entity is associated with or belongs to a particular club.
- 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5215ae3c81909e6dedba23822970 |
completed | April 27, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:34 p.m.