Triple

T15585335
Position Surface form Disambiguated ID Type / Status
Subject Hōzōmon E374605 entity
Predicate locatedIn P40 FINISHED
Object Asakusa 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: Asakusa | Statement: [Hōzōmon, locatedIn, Asakusa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asakusa
Context triple: [Hōzōmon, locatedIn, Asakusa]
  • A. Asakusa chosen
    Asakusa is a historic district in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
  • B. Asakusa district
    Asakusa district is a historic neighborhood in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
  • C. Komagome
    Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
  • D. Asagaya
    Asagaya is a residential and commercial neighborhood in Tokyo known for its traditional shopping streets, local festivals, and convenient access to central Tokyo.
  • E. Kamitabashi
    Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e4900408190aadb48b001db4169 completed April 16, 2026, 2:49 a.m.
Created at: April 10, 2026, 4:11 a.m.