Triple
T24288472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walnut Township, Russell County, Kansas |
E605740
|
entity |
| Predicate | followsCounty |
P13451
|
FINISHED |
| Object | Russell County regulations |
—
|
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: Russell County regulations | Statement: [Walnut Township, Russell County, Kansas, followsCounty, Russell County regulations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsCounty Context triple: [Walnut Township, Russell County, Kansas, followsCounty, Russell County regulations]
-
A.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
B.
inCounty
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
C.
hasNearbyCounty
Indicates that one county is geographically close to or directly adjacent to another county.
-
D.
sharesCountyWith
Indicates that two entities are located within the same county jurisdiction.
-
E.
associatedWithCounty
chosen
Indicates that an entity has a relationship or linkage to a specific county, such as jurisdiction, location, or administrative association.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f57a9a08190b183879ff76071d0 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.