Triple
T4940408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurt Buckman |
E110915
|
entity |
| Predicate | inUniverseOccupation |
P58964
|
FINISHED |
| Object | office worker |
—
|
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: office worker | Statement: [Kurt Buckman, inUniverseOccupation, office worker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inUniverseOccupation Context triple: [Kurt Buckman, inUniverseOccupation, office worker]
-
A.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
employerInUniverse
Indicates that one entity serves as the employer of another within a specified universe, context, or world.
-
C.
inUniverse
Indicates that one entity exists, occurs, or is set within the fictional or conceptual universe defined by another entity.
-
D.
hasInUniverseRole
chosen
Indicates that an entity holds or performs a specific role or function within a particular fictional or defined universe.
-
E.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd708a3dcc81908b6628864fe0db0a |
completed | March 20, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69bd6c389b9881908ad7fb1c5393c1b1 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.