Triple

T14948965
Position Surface form Disambiguated ID Type / Status
Subject Odori site E372739 entity
Predicate district P2709 FINISHED
Object Chuo-ku unclear NED1 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: Chuo-ku | Statement: [Odori site, district, Chuo-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chuo-ku
Context triple: [Odori site, district, 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
    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. chosen

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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded68fae3c81909873b113bfcaca05 completed April 15, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00b272ea6c8190b22fd78081446701 completed May 10, 2026, 4:29 p.m.
Created at: April 10, 2026, 2:39 a.m.