Triple

T23333137
Position Surface form Disambiguated ID Type / Status
Subject Osun State University (main campus vicinity) E591499 entity
Predicate partOf P40 FINISHED
Object Osun State University
Osun State University is a multi-campus public university in Osun State, Nigeria, known for its distributed campuses and diverse academic programs.
E1680141 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: Osun State University | Statement: [Osun State University (main campus vicinity), partOf, Osun State University]
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: Osun State University
Triple: [Osun State University (main campus vicinity), partOf, Osun State University]
Generated description
Osun State University is a multi-campus public university in Osun State, Nigeria, known for its distributed campuses and diverse academic programs.

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_69e25d20156c81908c5c53195bd9c738 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f197eecc5c81908089eb43bc701196 completed April 29, 2026, 5:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a108946065c8190a084764180ca30fc completed May 22, 2026, 4:50 p.m.
NEDg Description generation batch_6a108b13f26c81908a4d0ea4bdfa605c completed May 22, 2026, 4:57 p.m.
NED2 Entity disambiguation (via description) batch_6a108b8ea6908190b8f6887610e5d6a3 completed May 22, 2026, 4:59 p.m.
Created at: April 17, 2026, 5:16 p.m.