Triple
T29998077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reagan family |
E762084
|
entity |
| Predicate | hasMemberInOccupation |
P112780
|
FINISHED |
| Object | film actor (Ronald Reagan) |
—
|
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: film actor (Ronald Reagan) | Statement: [Reagan family, hasMemberInOccupation, film actor (Ronald Reagan)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberInOccupation Context triple: [Reagan family, hasMemberInOccupation, film actor (Ronald Reagan)]
-
A.
hasMemberWhoHeldOccupation
chosen
Indicates that a group or collective entity includes at least one member who has held a specified occupation.
-
B.
holderIsOccupation
Indicates that the holder entity has the specified occupation or job role.
-
C.
hasOccupationInWork
Indicates that an entity holds or performs a specific occupation within a particular work, project, or creative production.
-
D.
hasTypicalOccupation
Indicates that an entity commonly or characteristically works in a particular job or profession.
-
E.
hasIndustryRole
Indicates that an entity holds or performs a specific role, function, or position within a particular industry or sector.
- 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_69f224695498819094a81037cad401e2 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd6dbd1b648190b1a0b391c03aebc5 |
completed | May 8, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69fd6a9020548190bbfa845360ac85fb |
completed | May 8, 2026, 4:46 a.m. |
Created at: April 29, 2026, 6:40 p.m.