Triple

T11282195
Position Surface form Disambiguated ID Type / Status
Subject Takeshita Street E267090 entity
Predicate near P350 FINISHED
Object Omotesando E26236 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: Omotesando | Statement: [Takeshita Street, near, Omotesando]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Omotesando
Context triple: [Takeshita Street, near, Omotesando]
  • A. Omotesando chosen
    Omotesando is a fashionable, tree-lined avenue in central Tokyo known for its high-end boutiques, modern architecture, and trendy cafes.
  • B. Meiji-dori
    Meiji-dori is a major thoroughfare in Tokyo known for running through fashionable districts like Harajuku and connecting several key neighborhoods across the city.
  • C. Shimbashi
    Shimbashi is a major business and entertainment district in central Tokyo, known for its busy railway station, salaryman nightlife, and numerous izakaya bars.
  • D. Kyōbashi
    Kyōbashi is a historic commercial and business district in central Tokyo, located between Tokyo Station and the Ginza area.
  • E. Chūō-dōri shopping street
    Chūō-dōri shopping street is a major thoroughfare in Tokyo’s Akihabara district, famous for its dense concentration of electronics shops, anime and manga stores, and otaku culture attractions.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e96e15708190b3a1cccfbbe65882 completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e55639a5ec8190b979d5a280397f98 completed April 19, 2026, 10:24 p.m.
Created at: April 8, 2026, 9:31 p.m.