Triple
T33454453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chase County, Nebraska |
E856732
|
entity |
| Predicate | hasNamedAfterRole |
P157698
|
FINISHED |
| Object | U.S. Secretary of the Treasury |
—
|
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: U.S. Secretary of the Treasury | Statement: [Chase County, Nebraska, hasNamedAfterRole, U.S. Secretary of the Treasury]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamedAfterRole Context triple: [Chase County, Nebraska, hasNamedAfterRole, U.S. Secretary of the Treasury]
-
A.
hasNamedForRole
chosen
Indicates that an entity has been given a specific name or label that corresponds to a particular role it plays.
-
B.
hasNamesakeRoleFor
Indicates that one entity holds a role or position that is named after, or serves as a namesake for, another entity.
-
C.
hasNamedAfterPerson
Indicates that one entity is named in honor of, or derived from the name of, a specific person.
-
D.
hasSymbolNamedAfter
Indicates that one entity has a symbol whose name is derived from or dedicated to another entity.
-
E.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69feced53a7c819098ec474fb7d514b0 |
completed | May 9, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69fecd9cd5288190aac8b4e04a7ee78e |
completed | May 9, 2026, 6:01 a.m. |
Created at: May 1, 2026, 1:37 a.m.