Triple

T21352963
Position Surface form Disambiguated ID Type / Status
Subject Tokorozawa E526535 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Sayama 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: Sayama | Statement: [Tokorozawa, hasNeighboringMunicipality, Sayama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sayama
Context triple: [Tokorozawa, hasNeighboringMunicipality, Sayama]
  • A. Sayama chosen
    Sayama is a city in central Saitama Prefecture, Japan, known for its tea production and suburban residential character within the Greater Tokyo area.
  • B. Takashima
    Takashima is a lakeside city in western Shiga Prefecture, Japan, known for its scenic location along Lake Biwa and surrounding mountains.
  • C. Takashima
    Takashima is a prominent commercial and waterfront district in Nishi-ku, Yokohama, known for major shopping complexes and modern urban development.
  • D. Yumenoshima
    Yumenoshima is a reclaimed island in Tokyo Bay known for its parks, sports and recreational facilities, and former landfill history.
  • E. Mihama
    Mihama is a coastal town in Aichi Prefecture, Japan, known for its seaside scenery and role as part of the Chita Peninsula region.
  • 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8ad34a1d48190b14fa099968faf7c completed April 22, 2026, 11:12 a.m.
Created at: April 16, 2026, 5:05 p.m.