Triple

T12780119
Position Surface form Disambiguated ID Type / Status
Subject Chūō, Tokyo E305484 entity
Predicate contains P35 FINISHED
Object Harumi E569186 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: Harumi | Statement: [Chūō, Tokyo, contains, Harumi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harumi
Context triple: [Chūō, Tokyo, contains, Harumi]
  • A. Harumi chosen
    Harumi is a waterfront district in Tokyo’s Chūō ward known for its high-rise residential towers and role in the Tokyo 2020 Olympic and Paralympic Village.
  • B. Hisako
    Hisako is a member of the Japanese imperial family known as Princess Takamado, recognized for her cultural, charitable, and international goodwill activities.
  • C. Hiyō
    Hiyō was a Japanese aircraft carrier of the Imperial Japanese Navy that served in the Pacific Theater during World War II.
  • D. Haruko
    Haruko, better known as Empress Shōken, was the consort of Emperor Meiji and a prominent Japanese empress noted for her support of modernization and social welfare.
  • E. Noriko
    Noriko is a common Japanese feminine given name, often written with kanji conveying meanings such as "law," "order," or "child."
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e5a5680819095dcd491486d23e7 completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ebc75bc81908bad7fb06af674a9 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:29 p.m.