Triple

T34634119
Position Surface form Disambiguated ID Type / Status
Subject Sagamihara E889366 entity
Predicate hasUniversity P113 FINISHED
Object Bunkyo University Shonan Campus
Bunkyo University Shonan Campus is a Japanese university campus located in Sagamihara, Kanagawa Prefecture, known for its faculties in education, information, and communication.
E2107497 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: Bunkyo University Shonan Campus | Statement: [Sagamihara, hasUniversity, Bunkyo University Shonan 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: Bunkyo University Shonan Campus
Triple: [Sagamihara, hasUniversity, Bunkyo University Shonan Campus]
Generated description
Bunkyo University Shonan Campus is a Japanese university campus located in Sagamihara, Kanagawa Prefecture, known for its faculties in education, information, and communication.

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_69f349d724848190b63ad3407e0006d9 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7226aa5c081908fc693c6778462e7 completed May 3, 2026, 10:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3752e10d6881908624e834af3f9d59 completed June 21, 2026, 2:56 a.m.
NEDg Description generation batch_6a3753dfb2648190bced71780cfaffdd completed June 21, 2026, 3 a.m.
NED2 Entity disambiguation (via description) batch_6a37548530b4819091c423f83d8d387a completed June 21, 2026, 3:03 a.m.
Created at: May 1, 2026, 2:04 a.m.