Triple
T2580680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Thomas |
E57081
|
entity |
| Predicate | workEnvironment |
P853
|
FINISHED |
| Object | large-scale commercial interiors |
—
|
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: large-scale commercial interiors | Statement: [Roger Thomas, workEnvironment, large-scale commercial interiors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workEnvironment Context triple: [Roger Thomas, workEnvironment, large-scale commercial interiors]
-
A.
environmentType
chosen
Indicates the kind or category of environment associated with an entity or situation.
-
B.
locationOfWork
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
C.
employmentContext
Indicates the situational or organizational setting in which an employment relationship or work activity takes place.
-
D.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
E.
workScope
Indicates the defined range, extent, and boundaries of tasks or responsibilities involved in a particular work activity or project.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c6da888190ba7abfe37d182602 |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.