Triple

T17928015
Position Surface form Disambiguated ID Type / Status
Subject Tennoji-ku E448247 entity
Predicate adjacentTo P224 FINISHED
Object Chuo-ku NE NERFINISHED

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: Chuo-ku | Statement: [Tennoji-ku, adjacentTo, Chuo-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chuo-ku
Context triple: [Tennoji-ku, adjacentTo, Chuo-ku]
  • A. Chuo Ward
    Chuo Ward is a central administrative district of Kumamoto City in Japan, known for its role as a key commercial and civic hub of the area.
  • B. Chuo Ward chosen
    Chuo Ward is a central special ward of Tokyo, Japan, known for its major commercial districts like Ginza and Nihonbashi and its role as a key business and shopping hub.
  • C. Higashi-ku
    Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
  • D. Seo District
    Seo District is a western coastal district of Incheon, South Korea, known for its industrial complexes, port facilities, and growing residential areas.
  • E. Bunkyō-ku
    Bunkyō-ku is a central Tokyo ward known for its universities, cultural institutions, and quiet residential neighborhoods.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f79d14819095540856928f0e25 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4a5505af88190aa7a5cfee0baa3a4 completed April 19, 2026, 9:50 a.m.
Created at: April 10, 2026, 10:20 a.m.