Triple
T29435299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Affleck as George Reeves |
E746553
|
entity |
| Predicate | relatedRealPersonOccupation |
P12884
|
FINISHED |
| Object | film and television actor |
—
|
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 and television actor | Statement: [Ben Affleck as George Reeves, relatedRealPersonOccupation, film and television actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedRealPersonOccupation Context triple: [Ben Affleck as George Reeves, relatedRealPersonOccupation, film and television actor]
-
A.
namedPersonOccupation
chosen
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
B.
employerOfNotablePerson
Indicates that an entity serves or has served as the employer of a person who is considered notable.
-
C.
realPersonAffiliation
Indicates a relationship where a real person is formally associated or connected with an organization, group, or entity.
-
D.
involvedOccupationOf
Indicates that an entity participates in or is associated with a particular occupation or professional role.
-
E.
knownRelativesOccupation
Indicates that there is information about the occupations held by one or more relatives of a given 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a013a251b4081908b43d85dd95586c5 |
completed | May 11, 2026, 2:08 a.m. |
| PD | Predicate disambiguation | batch_6a0137e4ea988190812173a5ff044098 |
completed | May 11, 2026, 1:59 a.m. |
Created at: April 28, 2026, 3:16 p.m.