Triple

T11744421
Position Surface form Disambiguated ID Type / Status
Subject Tokyo 23 wards E279238 entity
Predicate hasMajorBusinessDistrict P459 FINISHED
Object Roppongi E72625 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: Roppongi | Statement: [Tokyo 23 wards, hasMajorBusinessDistrict, Roppongi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roppongi
Context triple: [Tokyo 23 wards, hasMajorBusinessDistrict, Roppongi]
  • A. Roppongi chosen
    Roppongi is a central Tokyo district famous for its vibrant nightlife, international community, and major art and entertainment complexes.
  • B. Akasaka
    Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
  • C. Shibuya
    Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
  • D. 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.
  • E. Roppongi Hills
    Roppongi Hills is a large urban redevelopment complex in Tokyo known for its skyscrapers, upscale shops, restaurants, offices, residences, and the Mori Art Museum.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4f2a38c8190a682d8dae1ab9415 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f72654dc88819095bc1ce23dfee4df completed May 3, 2026, 10:41 a.m.
Created at: April 8, 2026, 9:41 p.m.