Triple

T10521029
Position Surface form Disambiguated ID Type / Status
Subject Musashino E248168 entity
Predicate hasDistrict P459 FINISHED
Object Kichijoji E251908 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: Kichijoji | Statement: [Musashino, hasDistrict, Kichijoji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kichijoji
Context triple: [Musashino, hasDistrict, Kichijoji]
  • A. Kichijōji chosen
    Kichijōji is a popular Tokyo neighborhood known for its trendy shopping streets, vibrant dining and nightlife, and the expansive Inokashira Park.
  • B. Kawaguchi
    Kawaguchi is a major commuter city in the Greater Tokyo area of Japan, located just north of Tokyo in Saitama Prefecture.
  • C. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • D. Kisarazu
    Kisarazu is a coastal city in Chiba Prefecture, Japan, known as the mainland terminus of the Tokyo Bay Aqua-Line expressway.
  • E. Marunouchi
    Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509dec25881909bc748640f26a416 completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5e2b0408190866bbe9a3a56928b completed May 3, 2026, 4:58 a.m.
Created at: April 6, 2026, 12:28 p.m.