Triple

T16120826
Position Surface form Disambiguated ID Type / Status
Subject Ōi E391132 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Matsuda 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: Matsuda | Statement: [Ōi, neighboringMunicipality, Matsuda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matsuda
Context triple: [Ōi, neighboringMunicipality, Matsuda]
  • A. Matsuda chosen
    Matsuda is a small town in Kanagawa Prefecture, Japan, known for its scenic views of Mount Fuji and seasonal flower festivals.
  • B. Kanamachi
    Kanamachi is a neighborhood in Tokyo known as a residential and commercial area within the Katsushika ward.
  • C. Wakamatsu
    Wakamatsu is a ward in the city of Kitakyushu, Japan, known historically as a port and industrial area on the northern coast of Kyushu.
  • D. Wakatsuki
    Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
  • E. Kawaguchi
    Kawaguchi is a major commuter city in the Greater Tokyo area of Japan, located just north of Tokyo in Saitama Prefecture.
  • 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e20200acac8190a47e6a917ff8dd34 completed April 17, 2026, 9:48 a.m.
Created at: April 10, 2026, 5 a.m.