Triple

T27237959
Position Surface form Disambiguated ID Type / Status
Subject Tenrikyo Grand Festival E687117 entity
Predicate hasVenue P373 FINISHED
Object Main Sanctuary of Tenrikyo
The Main Sanctuary of Tenrikyo is the central place of worship and pilgrimage for followers of the Tenrikyo religion in Tenri, Japan.
E1763451 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: Main Sanctuary of Tenrikyo | Statement: [Tenrikyo Grand Festival, hasVenue, Main Sanctuary of Tenrikyo]
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: Main Sanctuary of Tenrikyo
Triple: [Tenrikyo Grand Festival, hasVenue, Main Sanctuary of Tenrikyo]
Generated description
The Main Sanctuary of Tenrikyo is the central place of worship and pilgrimage for followers of the Tenrikyo religion in Tenri, Japan.

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_69ef355547408190b5ca0d777c65040a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6267ae4608190b67b531b2e1aa2fe completed May 2, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a126274cccc8190986777be35565631 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a12689f20588190b04d6228164b2bf3 completed May 24, 2026, 2:55 a.m.
NED2 Entity disambiguation (via description) batch_6a126925c8488190b015e796b8e4202d completed May 24, 2026, 2:57 a.m.
Created at: April 27, 2026, 10:34 a.m.