Triple

T16558651
Position Surface form Disambiguated ID Type / Status
Subject 鶴舞地区 E402277 entity
Predicate locatedIn P40 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: [鶴舞地区, locatedIn, 名古屋市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 名古屋市
Context triple: [鶴舞地区, locatedIn, 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. Osaki City
    Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
  • D. Nichinan City
    Nichinan City is a coastal municipality in southern Miyazaki Prefecture, Japan, known for its scenic Nichinan Coast, subtropical climate, and historic sites such as Obi Castle Town.
  • E. Miyazaki City
    Miyazaki City is a coastal city in southeastern Kyushu, Japan, known for its mild climate, beaches, and role as an administrative and cultural center of the region.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3576bce0c819087ab36f7dec5c394 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067bcb698819092ede6ba4f8a4a2b completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:15 a.m.