Triple

T11744390
Position Surface form Disambiguated ID Type / Status
Subject Tokyo 23 wards E279238 entity
Predicate containsAdministrativeDivision P747 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: [Tokyo 23 wards, containsAdministrativeDivision, Shinjuku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shinjuku
Context triple: [Tokyo 23 wards, containsAdministrativeDivision, 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_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_69f62a6efa448190a9d95c5bd68ff34b completed May 2, 2026, 4:46 p.m.
Created at: April 8, 2026, 9:41 p.m.