Triple

T29111090
Position Surface form Disambiguated ID Type / Status
Subject Isabella County E736904 entity
Predicate hasFeature P182 FINISHED
Object Isabella County Courthouse
The Isabella County Courthouse is a historic government building in Isabella County, Michigan, that serves as the center for the county’s judicial and administrative functions.
E1852171 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: Isabella County Courthouse | Statement: [Isabella County, hasFeature, Isabella County Courthouse]
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: Isabella County Courthouse
Triple: [Isabella County, hasFeature, Isabella County Courthouse]
Generated description
The Isabella County Courthouse is a historic government building in Isabella County, Michigan, that serves as the center for the county’s judicial and administrative functions.

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_69f077ec765c81909474c88bcc8bab43 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f661be0108819090cae6a19ae4157d completed May 2, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2550525c9481908ca50288d0dcfec3 completed June 7, 2026, 11:04 a.m.
NEDg Description generation batch_6a2554568f388190960bbfb09ed37b1d completed June 7, 2026, 11:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2558e91cc0819081c9baa7e53d6f7e completed June 7, 2026, 11:41 a.m.
Created at: April 28, 2026, 11:18 a.m.