Triple

T8655297
Position Surface form Disambiguated ID Type / Status
Subject Asago E205398 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Yabu E148386 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: Yabu | Statement: [Asago, hasNeighboringMunicipality, Yabu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yabu
Context triple: [Asago, hasNeighboringMunicipality, Yabu]
  • A. Yabu chosen
    Yabu is a small city in northern Hyōgo Prefecture, Japan, known for its rural landscapes, hot springs, and access to mountainous outdoor recreation.
  • B. Yabun
    Yabun is a major annual Aboriginal and Torres Strait Islander cultural festival held in Sydney, celebrating Indigenous music, dance, and community.
  • C. Oyugis
    Oyugis is a town in western Kenya that serves as a key commercial and administrative center in the former Rachuonyo District of Homa Bay County.
  • D. Kagayaki
    Kagayaki is the fastest limited-stop train service operating on Japan’s Hokuriku Shinkansen line between Tokyo and the Hokuriku region.
  • E. Ogawa
    Ogawa is a town in Saitama Prefecture, Japan, known for its traditional Japanese paper (washi) production and its role as a local transport hub.
  • 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_69ca8350897c819086cde7596fbe5fe7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4844586081909b687e278496eefa completed March 31, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d178a6467c8190aab201fb12d2a64e completed April 4, 2026, 8:46 p.m.
Created at: March 30, 2026, 6:29 p.m.