Triple
T24300457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Damson Idris |
E606079
|
entity |
| Predicate | characterOccupationOfFranklinSaint |
P56368
|
FINISHED |
| Object | drug dealer |
—
|
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: drug dealer | Statement: [Damson Idris, characterOccupationOfFranklinSaint, drug dealer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterOccupationOfFranklinSaint Context triple: [Damson Idris, characterOccupationOfFranklinSaint, drug dealer]
-
A.
associatedSaintOccupation
Indicates the occupation or role that is linked to or held by a particular saint.
-
B.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
C.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
D.
patronOccupation
Indicates that one entity serves as the occupation or professional role held by a patron entity.
-
E.
notableCharacterOccupation
chosen
Indicates that a notable character is associated with a specific occupation or professional role.
- 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_69e29549335881909cbf27adcaba1cf0 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f2915e4ffc8190bf711dae443b3ec1 |
completed | April 29, 2026, 11:16 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 12:09 a.m.