Triple
T25830300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judicial Branch of Minnesota |
E650643
|
entity |
| Predicate | hasNumberOfBranchesInStateGovernment |
P172326
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Judicial Branch of Minnesota, hasNumberOfBranchesInStateGovernment, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfBranchesInStateGovernment Context triple: [Judicial Branch of Minnesota, hasNumberOfBranchesInStateGovernment, 3]
-
A.
representsBranchOfGovernment
Indicates that one entity functions as a branch within the governmental structure of another entity.
-
B.
associatedBranchOfGovernmentOfTitleHolder
Indicates the branch of government with which the holder of a given title is institutionally affiliated.
-
C.
hasNumberOfDeputies
Indicates the specific count of deputies associated with or assigned to an entity.
-
D.
hasNumberOfStatesAndDistricts
Indicates a relationship where an entity is associated with a specific count of its constituent states and districts.
-
E.
numberOfGovernment
Indicates the quantity of governmental bodies or administrations associated with an entity.
- F. None of above. chosen
Provenance (4 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6abe15d5c81909ccf4ce37f78bc43 |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1c555081908787dbf76147f180 |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aaf31a548190b2f792ff4b8c002a |
completed | May 3, 2026, 1:54 a.m. |
Created at: April 22, 2026, 7:38 a.m.