Triple

T38346963
Position Surface form Disambiguated ID Type / Status
Subject Greeley City Manager E1041569 entity
Predicate positionHeldInOrganization P8 FINISHED
Object City of Greeley government
The City of Greeley government is the municipal governing body responsible for administering public services, local policies, and city management for Greeley, Colorado.
E2269419 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: City of Greeley government | Statement: [Greeley City Manager, positionHeldInOrganization, City of Greeley government]
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: City of Greeley government
Triple: [Greeley City Manager, positionHeldInOrganization, City of Greeley government]
Generated description
The City of Greeley government is the municipal governing body responsible for administering public services, local policies, and city management for Greeley, Colorado.

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_69f76e2ad95481908c920c0e5c1c3e26 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc6f25f6c8190ad94f8178a08c5ca completed May 7, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41c27797148190a58d3db3b65de62b completed June 29, 2026, 12:55 a.m.
NEDg Description generation batch_6a41c3dac6ec81909231576db0b9808d completed June 29, 2026, 1:01 a.m.
NED2 Entity disambiguation (via description) batch_6a41c481f72c8190b44745166b1bb8c4 completed June 29, 2026, 1:04 a.m.
Created at: May 3, 2026, 4:30 p.m.