Triple

T10668670
Position Surface form Disambiguated ID Type / Status
Subject Chūichi Hara E251426 entity
Predicate hasFamilyName P18 FINISHED
Object Hara E827772 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: Hara | Statement: [Chūichi Hara, hasFamilyName, Hara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hara
Context triple: [Chūichi Hara, hasFamilyName, Hara]
  • A. Hara chosen
    Hara is a Japanese surname borne by various notable figures in politics, arts, and sports.
  • B. Haruna
    Haruna was a Japanese Kongō-class fast battleship that served in the Imperial Japanese Navy during both World Wars and saw extensive action in the Pacific Theater.
  • C. Hiranaka
    Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
  • D. Ihara
    Ihara is the Japanese family name of Ihara Saikaku, a prominent 17th-century Edo-period poet and writer known for his realistic portrayals of urban life.
  • E. Hisako
    Hisako is a member of the Japanese imperial family known as Princess Takamado, recognized for her cultural, charitable, and international goodwill activities.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6f860790c81909c2c1d3c489ec5b4 completed April 9, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69e712b2ff1081908ccf311e1133ab72 completed April 21, 2026, 6:01 a.m.
Created at: April 8, 2026, 9:09 p.m.