Triple

T36444130
Position Surface form Disambiguated ID Type / Status
Subject The University of Kansas Health System E897820 entity
Predicate isPartOf P10 FINISHED
Object Kansas health care system
Kansas health care system is the statewide network of medical providers, hospitals, and public health services that delivers and coordinates health care for residents across Kansas.
E2183918 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: Kansas health care system | Statement: [The University of Kansas Health System, isPartOf, Kansas health care system]
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: Kansas health care system
Triple: [The University of Kansas Health System, isPartOf, Kansas health care system]
Generated description
Kansas health care system is the statewide network of medical providers, hospitals, and public health services that delivers and coordinates health care for residents across Kansas.

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_69f76e5720b481908f8177ac24a7560b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd8aa06c8190bb9fe788af31b1c5 completed May 3, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c41f1ea88190a9ed0877c513dbf9 completed June 22, 2026, 11:24 p.m.
NEDg Description generation batch_6a39c4c69e8c81909a8d39b83926666f completed June 22, 2026, 11:27 p.m.
NED2 Entity disambiguation (via description) batch_6a39c59ba6d48190a285f5b0f1adcdda completed June 22, 2026, 11:30 p.m.
Created at: May 3, 2026, 4:10 p.m.