Triple
T29681061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WHO Goodwill Ambassador for Tuberculosis and HIV/AIDS |
E750951
|
entity |
| Predicate | typicalAppointee |
P94712
|
FINISHED |
| Object | public figure |
—
|
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: public figure | Statement: [WHO Goodwill Ambassador for Tuberculosis and HIV/AIDS, typicalAppointee, public figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAppointee Context triple: [WHO Goodwill Ambassador for Tuberculosis and HIV/AIDS, typicalAppointee, public figure]
-
A.
typicalAppointment
Indicates that an appointment represents a standard, usual, or commonly occurring scheduling arrangement between entities.
-
B.
typicalAppointmentContext
Indicates the usual situational setting or circumstances in which an appointment typically occurs.
-
C.
appointerType
Indicates the role or category of entity that has the authority to appoint another entity.
-
D.
typicalCaller
Indicates that one entity is the usual or most common initiator of calls or invocations to another entity.
-
E.
personType
chosen
Indicates that an entity is classified as a particular type or category of person.
- 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_69f0d624d7b08190ba237d226f78d0d9 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a02206665508190ae2324d253ccf377 |
completed | May 11, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_6a021fdc6e54819082847bedd97a680b |
completed | May 11, 2026, 6:28 p.m. |
Created at: April 28, 2026, 7:10 p.m.