Triple

T27108041
Position Surface form Disambiguated ID Type / Status
Subject Cornish College of the Arts E686634 entity
Predicate foundedBy P104 FINISHED
Object Nellie Cornish
Nellie Cornish was an American music educator and arts advocate who founded what became Cornish College of the Arts in Seattle.
 E1759624 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: Nellie Cornish | Statement: [Cornish College of the Arts, foundedBy, Nellie Cornish]
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: Nellie Cornish
Triple: [Cornish College of the Arts, foundedBy, Nellie Cornish]
Generated description
Nellie Cornish was an American music educator and arts advocate who founded what became Cornish College of the Arts in Seattle.

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_69ef148accd48190b6ed6e13a15f2a4f completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f623fef610819086a38b74d8c934b3 completed May 2, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1253754bd08190b55bed1f5eca0093 completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a125433c0288190ab1e54c3d763468d completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a1254f46d288190aa6f45f8c8e9007d completed May 24, 2026, 1:31 a.m.
Created at: April 27, 2026, 8:52 a.m.