Triple

T29682098
Position Surface form Disambiguated ID Type / Status
Subject College of Engineering and Applied Sciences E750979 entity
Predicate campus P269 FINISHED
Object Parkview Campus
Parkview Campus is the primary home of Western Michigan University's College of Engineering and Applied Sciences, featuring specialized facilities for engineering and technology education and research.
E1879740 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: Parkview Campus | Statement: [College of Engineering and Applied Sciences, campus, Parkview Campus]
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: Parkview Campus
Triple: [College of Engineering and Applied Sciences, campus, Parkview Campus]
Generated description
Parkview Campus is the primary home of Western Michigan University's College of Engineering and Applied Sciences, featuring specialized facilities for engineering and technology education and research.

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_69f0d624d7b08190ba237d226f78d0d9 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f6726281c08190a08d1f7a52c34a32 completed May 2, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267ec5d0a8819089c4d18d9f272d20 completed June 8, 2026, 8:35 a.m.
NEDg Description generation batch_6a2682d3fa3c81909e0736cb74338f7e completed June 8, 2026, 8:52 a.m.
NED2 Entity disambiguation (via description) batch_6a26883b773081908ee6cad8a66f0251 completed June 8, 2026, 9:15 a.m.
Created at: April 28, 2026, 7:11 p.m.