Triple

T1126204
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Metro Ginza Line E24724 entity
Predicate servesDistrict P82 FINISHED
Object Asakusa E72187 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: Asakusa | Statement: [Tokyo Metro Ginza Line, servesDistrict, Asakusa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asakusa
Context triple: [Tokyo Metro Ginza Line, servesDistrict, 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. Ueno
    Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
  • C. Bunkyo, Tokyo
    Bunkyo, Tokyo is a central special ward of Tokyo known for its educational institutions, cultural sites, and major sports venues such as the Tokyo Dome.
  • D. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • E. Ikebukuro
    Ikebukuro is a major commercial and entertainment district in Tokyo known for its large train station, shopping complexes, and vibrant youth culture.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdc2718819094f5519ffb56993b completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae0a966a6c81909d1d21c489340134 completed March 8, 2026, 11:47 p.m.
Created at: March 1, 2026, 7:44 p.m.