Triple
T9014451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American muralism |
E215556
|
entity |
| Predicate | typicalPatron |
P44199
|
FINISHED |
| Object | local governments in the United States |
—
|
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: local governments in the United States | Statement: [American muralism, typicalPatron, local governments in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPatron Context triple: [American muralism, typicalPatron, local governments in the United States]
-
A.
patronType
Indicates the classification or category of a patron in relation to a service, institution, or resource.
-
B.
primaryPatron
Indicates that one entity serves as the main or chief supporter, sponsor, or benefactor of another entity.
-
C.
probablePatron
Indicates that one entity is likely, but not certainly confirmed, to be the patron or sponsor of another entity.
-
D.
traditionalPatron
chosen
Indicates a relationship where one entity serves as a customary or historically established patron or supporter of another.
-
E.
typeOfPatronage
Indicates the specific kind or category of support, sponsorship, or backing that one entity provides to another.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69fae0b88190a0aa989bc37ab2c7 |
completed | April 1, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:06 p.m.