Triple

T11233399
Position Surface form Disambiguated ID Type / Status
Subject Shiba E265881 entity
Predicate adjacentTo P224 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: [Shiba, adjacentTo, Roppongi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roppongi
Context triple: [Shiba, adjacentTo, 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e903b8ec81909f9c89776d35c650 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6554d0b0081909cc031ff06b796c0 completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:30 p.m.