Triple

T10707438
Position Surface form Disambiguated ID Type / Status
Subject Asakusa Shrine E252443 entity
Predicate locatedIn P40 FINISHED
Object Taitō E34802 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: Taitō | Statement: [Asakusa Shrine, locatedIn, Taitō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taitō
Context triple: [Asakusa Shrine, locatedIn, Taitō]
  • A. Taitō chosen
    Taitō is a special ward in central Tokyo known for its historic districts, traditional temples, and major cultural attractions such as Ueno Park and Asakusa.
  • B. Task Force 64
    Task Force 64 was a U.S. Navy surface combat task force in the Pacific Theater during World War II, noted for its role in night battles such as those off Guadalcanal.
  • C. Kunio
    Kunio is a Japanese masculine given name borne by various notable figures in politics, academia, and the arts.
  • D. Tokitarō
    Tokitarō was the childhood given name of the renowned Japanese ukiyo-e artist Katsushika Hokusai.
  • E. Taikon
    Taikon is a Romani Swedish family name most prominently associated with activist and silversmith Rosa Taikon and her relatives.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fde080d48190830eaa863aad61ff completed April 9, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9990760b48190a05753974cdf556c completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:12 p.m.