Triple

T15498519
Position Surface form Disambiguated ID Type / Status
Subject Temple 52: Taisanji E378886 entity
Predicate hasHall P6080 FINISHED
Object Daishidō E1135792 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: Daishidō | Statement: [Temple 52: Taisanji, hasHall, Daishidō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daishidō
Context triple: [Temple 52: Taisanji, hasHall, Daishidō]
  • A. Daishidō chosen
    Daishidō is a hall within the Ryōzenji temple complex in Japan, typically dedicated to the revered Buddhist monk Kōbō Daishi.
  • B. Gaimushō
    Gaimushō is Japan’s Ministry of Foreign Affairs, responsible for managing the country’s diplomatic relations and international policies.
  • C. Daikoku
    Daikoku is a prominent Japanese deity of wealth, agriculture, and household prosperity, often depicted with a mallet and rice bales and revered as one of the Seven Lucky Gods.
  • D. Jūrakuji
    Jūrakuji is a Buddhist temple in Japan best known as Temple 7 on the Shikoku 88-temple pilgrimage route.
  • E. Shinto Taikyo
    Shinto Taikyo is a Shinto religious sect in Japan that emphasizes traditional Shinto rituals and teachings within the broader framework of Sect Shinto.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fb0aee081909db1c54349ec8492 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3667a53c81908be789f99e580265 completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:53 a.m.