Triple

T37495208
Position Surface form Disambiguated ID Type / Status
Subject Alaiedon Township, Michigan E931806 entity
Predicate borders P224 FINISHED
Object Onondaga Township, Michigan
Onondaga Township, Michigan is a rural civil township in Ingham County known for its agricultural landscape and small-community character in south-central Michigan.
E2259313 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: Onondaga Township, Michigan | Statement: [Alaiedon Township, Michigan, borders, Onondaga Township, Michigan]
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: Onondaga Township, Michigan
Triple: [Alaiedon Township, Michigan, borders, Onondaga Township, Michigan]
Generated description
Onondaga Township, Michigan is a rural civil township in Ingham County known for its agricultural landscape and small-community character in south-central Michigan.

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_69f76ec457a4819094eeb3aed9baac11 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba37f5d9881909c4cac49b6f625c0 completed May 6, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a417b13892c819080dcfe9760af13fd completed June 28, 2026, 7:50 p.m.
NEDg Description generation batch_6a417cf5bf7c8190af870a7117bfb53f completed June 28, 2026, 7:58 p.m.
NED2 Entity disambiguation (via description) batch_6a417d95219881909e74e704f7790758 completed June 28, 2026, 8:01 p.m.
Created at: May 3, 2026, 4:17 p.m.