Triple

T25535956
Position Surface form Disambiguated ID Type / Status
Subject Suwa City E640038 entity
Predicate knownFor P22 FINISHED
Object Suwa Taisha shrine complex
Suwa Taisha shrine complex is one of Japan’s oldest and most important Shinto shrine networks, famed for its unique rituals and deep historical significance in Nagano Prefecture.
E2099710 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: Suwa Taisha shrine complex | Statement: [Suwa City, knownFor, Suwa Taisha shrine complex]
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: Suwa Taisha shrine complex
Triple: [Suwa City, knownFor, Suwa Taisha shrine complex]
Generated description
Suwa Taisha shrine complex is one of Japan’s oldest and most important Shinto shrine networks, famed for its unique rituals and deep historical significance in Nagano Prefecture.

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_69e75dbfff7081909b0aa779d48321d2 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f89056b481908f02d5d6d2837bfd completed May 2, 2026, 1:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3729b8e0b08190a930e4d355b143f8 completed June 21, 2026, midnight
NEDg Description generation batch_6a372beefb9081908c8fe969e86599c4 completed June 21, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_6a372cb51db48190825e0b9114b84c4a completed June 21, 2026, 12:13 a.m.
Created at: April 21, 2026, 3:22 p.m.