Triple

T1195464
Position Surface form Disambiguated ID Type / Status
Subject Shibuya Station E25657 entity
Predicate servesDistrict P82 FINISHED
Object Shibuya entertainment district E208724 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: Shibuya entertainment district | Statement: [Shibuya Station, servesDistrict, Shibuya entertainment district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shibuya entertainment district
Context triple: [Shibuya Station, servesDistrict, Shibuya entertainment district]
  • A. Shibuya chosen
    Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
  • B. Roppongi
    Roppongi is a central Tokyo district famous for its vibrant nightlife, international community, and major art and entertainment complexes.
  • C. Otemachi
    Otemachi is a major business district in central Tokyo known for its concentration of corporate headquarters, financial institutions, and proximity to the Imperial Palace.
  • D. Akasaka
    Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd78f61c8190bdba2255d35a8fe4 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69af2b3a21248190aca7710ae6ad6478 completed March 9, 2026, 8:19 p.m.
Created at: March 1, 2026, 7:46 p.m.