Triple
T20913153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wayne County, Kentucky |
E515000
|
entity |
| Predicate | hasCountyNumberInState |
P106323
|
FINISHED |
| Object | one of 120 counties of Kentucky |
—
|
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: one of 120 counties of Kentucky | Statement: [Wayne County, Kentucky, hasCountyNumberInState, one of 120 counties of Kentucky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountyNumberInState Context triple: [Wayne County, Kentucky, hasCountyNumberInState, one of 120 counties of Kentucky]
-
A.
countyNumberInState
chosen
Indicates the ordinal position or identifying number assigned to a county within its state.
-
B.
hasCountyCode
Indicates that an entity is associated with a specific county identified by a standardized county code.
-
C.
hasCountyCodeType
Indicates that an entity is associated with a specific type or classification of county code.
-
D.
hasCountyNumberInKansas
Indicates that an entity is assigned a specific official county number within the state of Kansas.
-
E.
hasNumberOfCounties
Indicates the relationship that specifies how many counties are associated with or contained within a given 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec60d3288190897a087bbdd4f005 |
completed | April 21, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:48 p.m.