Triple

T27455028
Position Surface form Disambiguated ID Type / Status
Subject Kanto Gakuin University E692564 entity
Predicate hasCampus P116 FINISHED
Object Kanazawa-Hakkei Campus
Kanazawa-Hakkei Campus is a principal campus of Kanto Gakuin University in Yokohama, Japan, known for its coastal setting and comprehensive academic facilities.
 E1771931 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: Kanazawa-Hakkei Campus | Statement: [Kanto Gakuin University, hasCampus, Kanazawa-Hakkei 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: Kanazawa-Hakkei Campus
Triple: [Kanto Gakuin University, hasCampus, Kanazawa-Hakkei Campus]
Generated description
Kanazawa-Hakkei Campus is a principal campus of Kanto Gakuin University in Yokohama, Japan, known for its coastal setting and comprehensive academic facilities.

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_69ef5207903881909427745cda05d27a completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62dc89bfc81909987840a660f709f completed May 2, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b260e6f481909076075270653c1c completed May 24, 2026, 8:10 a.m.
NEDg Description generation batch_6a12b32353248190ac509d73a9910602 completed May 24, 2026, 8:13 a.m.
NED2 Entity disambiguation (via description) batch_6a12b3c695a0819099113dba54710362 completed May 24, 2026, 8:16 a.m.
Created at: April 27, 2026, 12:48 p.m.