Triple
T37390923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sumner County, Kansas |
E928701
|
entity |
| Predicate | followsCountyCode |
P10086
|
FINISHED |
| Object | Sumner County code SU |
—
|
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: Sumner County code SU | Statement: [Sumner County, Kansas, followsCountyCode, Sumner County code SU]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsCountyCode Context triple: [Sumner County, Kansas, followsCountyCode, Sumner County code SU]
-
A.
hasCountyCode
chosen
Indicates that an entity is associated with a specific county identified by a standardized county code.
-
B.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
C.
associatedWithCounty
Indicates that an entity has a relationship or linkage to a specific county, such as jurisdiction, location, or administrative association.
-
D.
subsequentCounty
Indicates that one county follows another in a defined sequence, such as chronological order of creation or administrative succession.
-
E.
hasNearbyCounty
Indicates that one county is geographically close to or directly adjacent to another county.
- 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_69f76ebb10c481909b54b9dba263e29f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff6fba1a5c8190a660279a6271d785 |
completed | May 9, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69ff6f59388c8190a7d6ab7bc7705bc0 |
completed | May 9, 2026, 5:31 p.m. |
Created at: May 3, 2026, 4:16 p.m.