Triple

T27374676
Position Surface form Disambiguated ID Type / Status
Subject Ramona, Kansas E691028 entity
Predicate hasJurisdiction P285 FINISHED
Object Marion County Sheriff's Office
The Marion County Sheriff's Office is a local law enforcement agency responsible for policing and public safety across Marion County, Kansas.
E1770172 NE 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: Marion County Sheriff's Office | Statement: [Ramona, Kansas, hasJurisdiction, Marion County Sheriff's Office]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Marion County Sheriff's Office
Triple: [Ramona, Kansas, hasJurisdiction, Marion County Sheriff's Office]
Generated description
The Marion County Sheriff's Office is a local law enforcement agency responsible for policing and public safety across Marion County, Kansas.

Provenance (5 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_69ef52022538819081f873d0c84a6dd6 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62c649f908190807c02d3f65942a4 completed May 2, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7e7de5c819089111fc4d4934798 completed May 24, 2026, 7:25 a.m.
NEDg Description generation batch_6a12a87492b48190be0461fafe4d081d completed May 24, 2026, 7:27 a.m.
NED2 Entity disambiguation (via description) batch_6a12a926a67c819083713f0245b3e299 completed May 24, 2026, 7:30 a.m.
Created at: April 27, 2026, 12:20 p.m.