Triple

T38085872
Position Surface form Disambiguated ID Type / Status
Subject Kasugayama Castle E950974 entity
Predicate near P350 FINISHED
Object Kasugayama Shrine
Kasugayama Shrine is a Shinto shrine in Joetsu, Niigata Prefecture, Japan, historically associated with the warlord Uesugi Kenshin and the former Kasugayama Castle.
E2292233 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: Kasugayama Shrine | Statement: [Kasugayama Castle, near, Kasugayama Shrine]
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: Kasugayama Shrine
Triple: [Kasugayama Castle, near, Kasugayama Shrine]
Generated description
Kasugayama Shrine is a Shinto shrine in Joetsu, Niigata Prefecture, Japan, historically associated with the warlord Uesugi Kenshin and the former Kasugayama Castle.

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_69f76f03a3608190a73fd6df87c792a8 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc456f33048190a303b87c366a64c8 completed May 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5cd53a5e308190882815ce91e0eacc completed July 19, 2026, 1:46 p.m.
NEDg Description generation batch_6a5cd5ab7a0c8190aebf4108f4400ef6 completed July 19, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_6a5cd627f58c8190b1511b8ba858f69a completed July 19, 2026, 1:50 p.m.
Created at: May 3, 2026, 4:21 p.m.