Triple

T38081135
Position Surface form Disambiguated ID Type / Status
Subject Viborg, South Dakota E950853 entity
Predicate hasEducationalInstitution P113 FINISHED
Object Viborg-Hurley School District
Viborg-Hurley School District is a public school district serving students in the Viborg and Hurley communities in southeastern South Dakota.
E2254430 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: Viborg-Hurley School District | Statement: [Viborg, South Dakota, hasEducationalInstitution, Viborg-Hurley School District]
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: Viborg-Hurley School District
Triple: [Viborg, South Dakota, hasEducationalInstitution, Viborg-Hurley School District]
Generated description
Viborg-Hurley School District is a public school district serving students in the Viborg and Hurley communities in southeastern South Dakota.

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_69f76f03a3608190a73fd6df87c792a8 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc456b4e6c8190bec94fe1d2a558c4 completed May 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a415d4a1820819099b04a1a6c03c34a completed June 28, 2026, 5:43 p.m.
NEDg Description generation batch_6a415dfc9b308190b75033cd89dd1a1f completed June 28, 2026, 5:46 p.m.
NED2 Entity disambiguation (via description) batch_6a415f54846081909b862a6d8c2cc73a completed June 28, 2026, 5:52 p.m.
Created at: May 3, 2026, 4:21 p.m.