Triple

T1126201
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Metro Ginza Line E24724 entity
Predicate servesDistrict P82 FINISHED
Object Ginza E71727 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: Ginza | Statement: [Tokyo Metro Ginza Line, servesDistrict, Ginza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ginza
Context triple: [Tokyo Metro Ginza Line, servesDistrict, Ginza]
  • A. Ginza chosen
    Ginza is a famous upscale shopping, dining, and entertainment district in central Tokyo known for its luxury boutiques, department stores, and vibrant nightlife.
  • B. Toranomon
    Toranomon is a central business district in Tokyo known for its government offices, corporate headquarters, and proximity to major transport and commercial hubs.
  • C. Akasaka
    Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
  • D. Asakusa
    Asakusa is a historic district in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
  • E. Shinjuku
    Shinjuku is a major commercial and entertainment district in western Tokyo, known for its busy railway station, skyscrapers, shopping, nightlife, and the Tokyo Metropolitan Government Building.
  • 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_69ae589f5c588190a207ffa2691490b7 completed March 9, 2026, 5:20 a.m.
Created at: March 1, 2026, 7:44 p.m.