Triple

T2202791
Position Surface form Disambiguated ID Type / Status
Subject Japanese Alps E50527 entity
Predicate nearbyCity P350 FINISHED
Object Toyama E208642 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: Toyama | Statement: [Japanese Alps, nearbyCity, Toyama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyama
Context triple: [Japanese Alps, nearbyCity, Toyama]
  • A. Toyama chosen
    Toyama is a coastal city in central Japan known as the capital of Toyama Prefecture, serving as a regional industrial and transportation hub on the Sea of Japan.
  • B. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • C. Oita
    Ōita is a coastal city on Japan’s Kyushu island known for its hot springs, regional cuisine, and role as the capital of Ōita Prefecture.
  • D. Niigata
    Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
  • E. Ayabe
    Ayabe is a small city in the northern part of Japan’s Kyoto Prefecture, known for its rural landscapes, traditional industries, and spiritual retreat centers.
  • 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_69a88b044ab48190add007487680f009 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfa33f0881908403604eafb73ecf completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69bed8f0f4088190ba66d5e3c6642c9a completed March 21, 2026, 5:44 p.m.
Created at: March 4, 2026, 7:46 p.m.