Triple
T21334319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorothy Bracken |
E525998
|
entity |
| Predicate | partnerOccupation |
P4765
|
FINISHED |
| Object | comedian |
—
|
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: comedian | Statement: [Dorothy Bracken, partnerOccupation, comedian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partnerOccupation Context triple: [Dorothy Bracken, partnerOccupation, comedian]
-
A.
partnerInProfession
Indicates that two or more entities share a professional partnership or collaborate together within the same occupation or field.
-
B.
parentOccupation
Indicates that one entity has an occupation which is the job or profession of the other entity’s parent.
-
C.
spouseOccupation
chosen
Indicates that one person’s spouse has a particular job, profession, or occupation.
-
D.
recipientOccupation
Indicates that the object specifies the job, profession, or role held by the recipient in the described relationship or event.
-
E.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- 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_69e0b51b90788190a4dd823d962626da |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5ba7ce3c8190ba5ded980a9866f2 |
completed | April 26, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e6161feea4819091d13bb003363279 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 4:43 p.m.