Triple

T15109479
Position Surface form Disambiguated ID Type / Status
Subject Seibu Ikebukuro E360873 entity
Predicate serves P98 FINISHED
Object Ikebukuro district E73529 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: Ikebukuro district | Statement: [Seibu Ikebukuro, serves, Ikebukuro district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ikebukuro district
Context triple: [Seibu Ikebukuro, serves, Ikebukuro district]
  • A. Ikebukuro chosen
    Ikebukuro is a major commercial and entertainment district in Tokyo known for its large train station, shopping complexes, and vibrant youth culture.
  • B. Ueno district
    Ueno district is a cultural and historical area in Tokyo known for its major museums, temples, and the expansive Ueno Park.
  • C. Aoyama district
    Aoyama district is an upscale neighborhood in central Tokyo known for its fashionable boutiques, trendy cafes, art galleries, and modern architecture.
  • D. Tamagawa district
    Tamagawa district is a residential neighborhood in Setagaya, Tokyo, known for its riverside location along the Tama River and relatively tranquil urban atmosphere.
  • E. Itabashi
    Itabashi is a special ward in northern Tokyo, Japan, known as a primarily residential area with a mix of traditional neighborhoods and modern urban infrastructure.
  • 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_69d85a0491ec8190830960be8fafb994 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0058c04f481909deeac0271d961b6 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a502c82881908d5b6f7c23e8a403 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 3:05 a.m.