Triple

T32178361
Position Surface form Disambiguated ID Type / Status
Subject Anoka County Library – Coon Rapids branch E821916 entity
Predicate partOf P40 FINISHED
Object Anoka County Library
Anoka County Library is a public library system serving residents of Anoka County, Minnesota through multiple community branches and services.
E1995071 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: Anoka County Library | Statement: [Anoka County Library – Coon Rapids branch, partOf, Anoka County Library]
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: Anoka County Library
Triple: [Anoka County Library – Coon Rapids branch, partOf, Anoka County Library]
Generated description
Anoka County Library is a public library system serving residents of Anoka County, Minnesota through multiple community branches and 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_69f3490755288190aee11740a34862f9 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6ba7b13b481908a3658adff04878c completed May 3, 2026, 3:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0be0fbe88190a1f34d8f161ca607 completed June 14, 2026, 8:15 p.m.
NEDg Description generation batch_6a2f15c01ddc8190917b27116de5192e completed June 14, 2026, 8:57 p.m.
NED2 Entity disambiguation (via description) batch_6a2f161bae0c81908f76582676bdf681 completed June 14, 2026, 8:59 p.m.
Created at: May 1, 2026, 12:34 a.m.