Triple

T12734519
Position Surface form Disambiguated ID Type / Status
Subject Shinjuku Sumitomo Building E304328 entity
Predicate ward P21208 FINISHED
Object Shinjuku E69504 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: Shinjuku | Statement: [Shinjuku Sumitomo Building, ward, Shinjuku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shinjuku
Context triple: [Shinjuku Sumitomo Building, ward, Shinjuku]
  • A. Shinjuku chosen
    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.
  • B. Shibuya
    Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
  • C. Akasaka
    Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
  • D. Shinagawa
    Shinagawa is a major commercial and transportation hub in Tokyo, Japan, known for its busy railway station, business districts, and waterfront developments.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9646b3ca08190b239f0736a01169d completed April 10, 2026, 8:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce5b2b988190892e14620fb87366 completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 5:26 p.m.