Triple

T36897408
Position Surface form Disambiguated ID Type / Status
Subject Macomb County Jail E911927 entity
Predicate detainsFor P33388 FINISHED
Object Macomb County courts
Macomb County courts are the judicial bodies in Macomb County, Michigan, responsible for handling local criminal, civil, family, and traffic cases.
E265263 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: Macomb County courts | Statement: [Macomb County Jail, detainsFor, Macomb County courts]
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: Macomb County courts
Triple: [Macomb County Jail, detainsFor, Macomb County courts]
Generated description
Macomb County courts are the judicial bodies in Macomb County, Michigan, responsible for handling local criminal, civil, family, and traffic cases.

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_69f76e841b54819097e7fa768bbc70b2 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fd90b15c8190801dffdc65d39c78 completed May 5, 2026, 2:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfafa767481908f189cef43e67d16 completed June 26, 2026, 4:07 a.m.
NEDg Description generation batch_6a3dfd5aa9788190af71bb5c6a7af107 completed June 26, 2026, 4:17 a.m.
NED2 Entity disambiguation (via description) batch_6a3e02af021481908d97618a61ce8d54 completed June 26, 2026, 4:40 a.m.
Created at: May 3, 2026, 4:13 p.m.