Triple

T1360088
Position Surface form Disambiguated ID Type / Status
Subject Nagatachō E29078 entity
Predicate adjacentTo P224 FINISHED
Object Hanzōmon area E91784 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: Hanzōmon area | Statement: [Nagatachō, adjacentTo, Hanzōmon area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanzōmon area
Context triple: [Nagatachō, adjacentTo, Hanzōmon area]
  • A. Hanzōmon area chosen
    The Hanzōmon area is a central Tokyo district near the Imperial Palace, known for its government offices, media companies, and relatively quiet, upscale residential atmosphere.
  • B. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • C. Kitano-cho
    Kitano-cho is a historic district in Kobe, Japan, known for its preserved Western-style residences built by foreign merchants in the late 19th and early 20th centuries.
  • D. Tsuzuki District
    Tsuzuki District is a former administrative district that once existed within Kyoto Prefecture in Japan.
  • E. Tempozan district
    Tempozan district is a waterfront area in Osaka, Japan, known for attractions such as the Tempozan Ferris Wheel and Osaka Aquarium Kaiyukan.
  • 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_69a498d77abc8190913bf57e5f51d2c4 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c2b156b081909c99ada70a969fc0 completed March 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce725fec819085f6de8e6e368aa4 completed March 8, 2026, 1:18 a.m.
Created at: March 1, 2026, 7:56 p.m.