Triple

T21466830
Position Surface form Disambiguated ID Type / Status
Subject 堀越 二郎 E529613 entity
Predicate workLocation P7 FINISHED
Object 名古屋市 E11598 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: 名古屋市 | Statement: [堀越 二郎, workLocation, 名古屋市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 名古屋市
Context triple: [堀越 二郎, workLocation, 名古屋市]
  • A. 熊本市
    熊本市 is the capital and largest city of Kumamoto Prefecture on Japan’s Kyushu island, known for its historic Kumamoto Castle and rich samurai-era heritage.
  • B. Nagoya chosen
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • C. Nankoku City
    Nankoku City is a regional city on the island of Shikoku in Japan, known for its agricultural production and proximity to the city of Kōchi.
  • D. Osaki City
    Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
  • E. 豊川市
    豊川市 is a city in eastern Aichi Prefecture, Japan, known for Toyokawa Inari Shrine and its mix of industrial activity and rich historical culture.
  • 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_69e0c458133481908ae8b41a12c4edec completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9f32b5c8190bfa5acb3c9b1ab3b completed April 23, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09cff53c5c8190824b561ed79da378 completed May 17, 2026, 2:25 p.m.
Created at: April 16, 2026, 6:13 p.m.