Triple

T29585673
Position Surface form Disambiguated ID Type / Status
Subject Cleveland County government E754012 entity
Predicate hasOffice P1268 FINISHED
Object Cleveland County Sheriff
The Cleveland County Sheriff is the chief law enforcement official responsible for policing, jail operations, and related public safety services within Cleveland County.
E1874278 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: Cleveland County Sheriff | Statement: [Cleveland County government, hasOffice, Cleveland 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: Cleveland County Sheriff
Triple: [Cleveland County government, hasOffice, Cleveland County Sheriff]
Generated description
The Cleveland County Sheriff is the chief law enforcement official responsible for policing, jail operations, and related public safety services within Cleveland County.

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_69f0ef836ac88190bd809dc58b5ec907 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66d7dfb948190b35070cef785d6b8 completed May 2, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a262d76941c81909e409f9551451ff4 completed June 8, 2026, 2:48 a.m.
NEDg Description generation batch_6a26323b299c8190b37d3bf619dfc0d6 completed June 8, 2026, 3:08 a.m.
NED2 Entity disambiguation (via description) batch_6a26363f5bac81908fa2a4199ceb3f17 completed June 8, 2026, 3:25 a.m.
Created at: April 28, 2026, 6:10 p.m.