Triple
T32512750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mister Donut |
E830979
|
entity |
| Predicate | formerRegionOfOperation |
P6665
|
FINISHED |
| Object | North America |
—
|
NE NERFINISHED |
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: North America | Statement: [Mister Donut, formerRegionOfOperation, North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerRegionOfOperation Context triple: [Mister Donut, formerRegionOfOperation, North America]
-
A.
operatedInRegion
chosen
Indicates that an entity conducted operations or activities within a specified geographic region.
-
B.
formerServesRegion
Indicates that an entity previously served, represented, or had official responsibility for a given region, but no longer does so.
-
C.
formerRegionBefore2016
Indicates that an entity was recognized as a region prior to the year 2016 but no longer holds that regional status after 2016.
-
D.
historicalOperationRegion
Indicates the geographic area in which an entity carried out its activities or operations during a past or historical period.
-
E.
formerNameOfRegion
Indicates that one name was previously used for a region that is now known by a different name.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff7fc835f08190afd1f8129b7a62a2 |
completed | May 9, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
Created at: May 1, 2026, 1 a.m.