Triple

T34298296
Position Surface form Disambiguated ID Type / Status
Subject Government of Sioux Falls E880094 entity
Predicate oversees P46 FINISHED
Object Health Department of Sioux Falls
The Health Department of Sioux Falls is the municipal agency responsible for protecting and promoting public health for residents of Sioux Falls, South Dakota.
E2089127 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: Health Department of Sioux Falls | Statement: [Government of Sioux Falls, oversees, Health Department of Sioux Falls]
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: Health Department of Sioux Falls
Triple: [Government of Sioux Falls, oversees, Health Department of Sioux Falls]
Generated description
The Health Department of Sioux Falls is the municipal agency responsible for protecting and promoting public health for residents of Sioux Falls, 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_69f349b79f6c81909cb468c92c39c74d completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71333b86c81909c0e739fb85b9a2d completed May 3, 2026, 9:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36e637e0b48190a785e46bb6a70d03 completed June 20, 2026, 7:12 p.m.
NEDg Description generation batch_6a36e93435048190b51cb9e7ecab281c completed June 20, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_6a36e9bb55ac819087e417973a23fa0b completed June 20, 2026, 7:27 p.m.
Created at: May 1, 2026, 1:57 a.m.