Triple
T22316229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leo Farnsworth |
E551650
|
entity |
| Predicate | primarySettingOfWealth |
P14490
|
FINISHED |
| Object | corporate business world |
—
|
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: corporate business world | Statement: [Leo Farnsworth, primarySettingOfWealth, corporate business world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySettingOfWealth Context triple: [Leo Farnsworth, primarySettingOfWealth, corporate business world]
-
A.
primarySettingOf
chosen
Indicates that a location or context serves as the main or principal setting in which an entity (such as a story, event, or activity) takes place.
-
B.
primarySetting
Indicates that one entity serves as the main or central location, context, or environment in which the other entity’s events or activities primarily take place.
-
C.
primaryTrade
Indicates that the referenced activity or exchange is the main or most significant trade relationship associated with the entities involved.
-
D.
primarySettingFeature
Indicates that a particular feature is the main or defining characteristic of a setting.
-
E.
primaryAsset
Indicates that one entity is the main or most important asset associated with another entity.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157535eb48190adbefbb619cb5fcd |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:42 p.m.