Triple

T27864036
Position Surface form Disambiguated ID Type / Status
Subject Lake County government E704305 entity
Predicate hasElectedOfficial P1239 FINISHED
Object Lake County Sheriff
The Lake County Sheriff is the chief law enforcement officer for Lake County, responsible for overseeing countywide policing, jail operations, and related public safety services.
E1243763 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: Lake County Sheriff | Statement: [Lake County government, hasElectedOfficial, Lake County Sheriff]
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: Lake County Sheriff
Triple: [Lake County government, hasElectedOfficial, Lake County Sheriff]
Generated description
The Lake County Sheriff is the chief law enforcement officer for Lake County, responsible for overseeing countywide policing, jail operations, and related public safety services.

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_69ef840f12408190b539d00d79658abf completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63946708881908e441f37c8bd6fee completed May 2, 2026, 5:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13034cf44881909b6ff34124b70b35 completed May 24, 2026, 1:55 p.m.
NEDg Description generation batch_6a130713a35c8190be62e0e39405e91c completed May 24, 2026, 2:11 p.m.
NED2 Entity disambiguation (via description) batch_6a13078a49448190901f8eb8e74111f6 completed May 24, 2026, 2:13 p.m.
Created at: April 27, 2026, 6:19 p.m.