Triple
T24743563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon County |
E618630
|
entity |
| Predicate | hasNamedForRole |
P157698
|
FINISHED |
| Object | U.S. Senator |
—
|
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. Senator | Statement: [Lyon County, hasNamedForRole, U.S. Senator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamedForRole Context triple: [Lyon County, hasNamedForRole, U.S. Senator]
-
A.
hasNamesakeRoleFor
Indicates that one entity holds a role or position that is named after, or serves as a namesake for, another entity.
-
B.
isNamedForEponymRole
Indicates that one entity bears a name derived from another entity that serves as its eponym or namesake.
-
C.
namedIn
Indicates that one entity is explicitly mentioned or referenced by name within another entity (such as a document, statement, or record).
-
D.
hasNameGivenTo
Indicates that one entity is the name that has been assigned or given to another entity.
-
E.
hasGivenNameTo
Indicates that one entity has assigned or provided a given (first) name to another 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f44a3adb7c8190941572f718b3b93c |
completed | May 1, 2026, 6:37 a.m. |
Created at: April 18, 2026, 4:19 a.m.