Triple

T33633400
Position Surface form Disambiguated ID Type / Status
Subject Hazard, Kentucky E861625 entity
Predicate hasPublicSchoolDistrict P226 FINISHED
Object Hazard Independent Schools
Hazard Independent Schools is a small public school district serving students in and around the city of Hazard in eastern Kentucky.
E2059779 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: Hazard Independent Schools | Statement: [Hazard, Kentucky, hasPublicSchoolDistrict, Hazard Independent Schools]
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: Hazard Independent Schools
Triple: [Hazard, Kentucky, hasPublicSchoolDistrict, Hazard Independent Schools]
Generated description
Hazard Independent Schools is a small public school district serving students in and around the city of Hazard in eastern Kentucky.

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_69f34981c54c81909b33c3fa2208a52d completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f97088488190962e81c5299f830b completed May 3, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3611b1ecd481908341266508748de1 completed June 20, 2026, 4:06 a.m.
NEDg Description generation batch_6a36132d83388190ad93116a55fd2491 completed June 20, 2026, 4:12 a.m.
NED2 Entity disambiguation (via description) batch_6a36139a720881909d4face878e7a88d completed June 20, 2026, 4:14 a.m.
Created at: May 1, 2026, 1:41 a.m.