Triple

T17436495
Position Surface form Disambiguated ID Type / Status
Subject Madadayo E424013 entity
Predicate title P38 FINISHED
Object Madadayo NE NERFINISHED

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: Madadayo | Statement: [Madadayo, title, Madadayo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madadayo
Context triple: [Madadayo, title, Madadayo]
  • A. Madadayo chosen
    Madadayo is a 1993 Japanese drama film directed by Akira Kurosawa that poignantly portrays the later years of a beloved professor and his enduring bond with former students.
  • B. Kauyumari
    Kauyumari is a central deer spirit and cultural hero in Wixárika (Huichol) religion, associated with guidance, creation, and the connection between humans, nature, and the sacred.
  • C. Hieda no Are
    Hieda no Are was a Japanese court reciter traditionally credited with memorizing the oral histories that formed the basis of the early 8th-century chronicle Kojiki.
  • D. Madadeni
    Madadeni is a township in KwaZulu-Natal, South Africa, situated near Newcastle and known as a large residential and industrial area in the region.
  • E. Kudanshita
    Kudanshita is a district and major subway station area in central Tokyo known for its proximity to the Imperial Palace, Yasukuni Shrine, and several universities and office buildings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4490426008190b474ed76aca5d6f3 completed April 19, 2026, 3:16 a.m.
Created at: April 10, 2026, 5:46 a.m.