Triple

T34810585
Position Surface form Disambiguated ID Type / Status
Subject Donald P. Shiley E1003487 entity
Predicate hasLegacy P267 FINISHED
Object Shiley-Marcos School of Engineering at University of San Diego
The Shiley-Marcos School of Engineering at the University of San Diego is a private, student-centered engineering school known for combining rigorous technical education with a strong emphasis on ethics, innovation, and hands-on learning.
 E63548 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: Shiley-Marcos School of Engineering at University of San Diego | Statement: [Donald P. Shiley, hasLegacy, Shiley-Marcos School of Engineering at University of San Diego]
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: Shiley-Marcos School of Engineering at University of San Diego
Triple: [Donald P. Shiley, hasLegacy, Shiley-Marcos School of Engineering at University of San Diego]
Generated description
The Shiley-Marcos School of Engineering at the University of San Diego is a private, student-centered engineering school known for combining rigorous technical education with a strong emphasis on ethics, innovation, and hands-on learning.

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_69f76db600b88190989abdf08fce3b27 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77ab4a9dc8190ad41fb613f35ddad completed May 3, 2026, 4:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d9341d048190b0f208e97fa0eba5 completed June 21, 2026, 12:29 p.m.
NEDg Description generation batch_6a37da28a3bc8190b36abb1d36a5c930 completed June 21, 2026, 12:33 p.m.
NED2 Entity disambiguation (via description) batch_6a37db99ec64819084312c5bc5269fe3 completed June 21, 2026, 12:39 p.m.
Created at: May 3, 2026, 3:59 p.m.