Triple

T13343723
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Engineering, Hosei University E317890 entity
Predicate city P40 FINISHED
Object Koganei 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: Koganei | Statement: [Faculty of Engineering, Hosei University, city, Koganei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koganei
Context triple: [Faculty of Engineering, Hosei University, city, Koganei]
  • A. Hachiōji
    Hachiōji is a city in western Tokyo, Japan, known as a regional commercial and educational hub with rich historical sites and access to nearby mountains and nature.
  • B. Chōfu
    Chōfu is a suburban city in western Tokyo, Japan, known for its residential neighborhoods, film studios, and proximity to central Tokyo.
  • C. Koganei, Tokyo chosen
    Koganei, Tokyo is a suburban city in western Tokyo Metropolis known for its residential neighborhoods, parks, and the renowned Edo-Tokyo Open Air Architectural Museum in Koganei Park.
  • D. Musashino
    Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
  • E. Kōtō
    Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8839b48190b164414b418e756c completed April 11, 2026, 1:06 a.m.
Created at: April 9, 2026, 9:31 p.m.