Triple

T33903022
Position Surface form Disambiguated ID Type / Status
Subject Mount Vernon, Iowa E869098 entity
Predicate governingBody P46 FINISHED
Object Mount Vernon City Council
The Mount Vernon City Council is the elected municipal legislative body responsible for setting policies, passing ordinances, and overseeing local governance in Mount Vernon, Iowa.
E2072588 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: Mount Vernon City Council | Statement: [Mount Vernon, Iowa, governingBody, Mount Vernon City Council]
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: Mount Vernon City Council
Triple: [Mount Vernon, Iowa, governingBody, Mount Vernon City Council]
Generated description
The Mount Vernon City Council is the elected municipal legislative body responsible for setting policies, passing ordinances, and overseeing local governance in Mount Vernon, Iowa.

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_69f34997703c8190866b1d404bce531f completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70184a4d081908a11fdf7a221c302 completed May 3, 2026, 8:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3682442c088190a5aef5e07a81962d completed June 20, 2026, 12:06 p.m.
NEDg Description generation batch_6a3682b7fc1c8190a05b0f1682f32782 completed June 20, 2026, 12:08 p.m.
NED2 Entity disambiguation (via description) batch_6a368327e7248190801ee93ba760d704 completed June 20, 2026, 12:10 p.m.
Created at: May 1, 2026, 1:48 a.m.