Triple
T23617121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandela United Football Club |
E583204
|
entity |
| Predicate | TRCCharacterization |
P153284
|
FINISHED |
| Object | criminal gang |
—
|
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: criminal gang | Statement: [Mandela United Football Club, TRCCharacterization, criminal gang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: TRCCharacterization Context triple: [Mandela United Football Club, TRCCharacterization, criminal gang]
-
A.
theoryCharacterization
Indicates that one entity provides a defining description, formulation, or account of a theory associated with another entity.
-
B.
resultCharacterization
Indicates how the outcome of an event, process, or action is qualitatively described or characterized.
-
C.
studyCharacterization
Indicates a relationship where an entity conducts a detailed examination or analysis to characterize or define the properties, behavior, or features of another entity.
-
D.
sourceCharacterization
Indicates that one entity describes, explains, or characterizes the origin, provenance, or source of another entity.
-
E.
trialCharacterization
Indicates the specific features, conditions, or parameters that define and distinguish a particular trial within an experimental or procedural context.
- 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_69e248fbcd9081908ba08913f9d30826 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b175b2208190a78e1d4aac191709 |
completed | April 29, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f138b8c9248190b059bc38a9a50958 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 17, 2026, 6:45 p.m.