Triple

T13353350
Position Surface form Disambiguated ID Type / Status
Subject Japanese occupation of Hainan E318124 entity
Predicate appliesToJurisdiction P82 FINISHED
Object Hainan E37179 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: Hainan | Statement: [Japanese occupation of Hainan, appliesToJurisdiction, Hainan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hainan
Context triple: [Japanese occupation of Hainan, appliesToJurisdiction, Hainan]
  • A. Hainan chosen
    Hainan is a tropical island province in southern China known for its beaches, tourism, and status as a major special economic zone.
  • B. Hainan Hlai
    Hainan Hlai is a Kra–Dai language spoken primarily by the Li (Hlai) ethnic group on China’s Hainan Island.
  • C. Hainan Special Economic Zone
    Hainan Special Economic Zone is a major Chinese free-trade and investment zone encompassing the entire island province of Hainan, established to promote market-oriented economic reforms and international commerce.
  • D. Lingshui
    Lingshui is a coastal county-level city in southeastern Hainan, China, known for its tropical climate, beaches, and growing tourism industry.
  • E. Qizhou
    Qizhou is a historic town in Hubei, China, known as the birthplace of the famed Ming dynasty physician and pharmacologist Li Shizhen.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8d520881908aa23c7102b72b72 completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f72675c87c8190b26991b55092c444 completed May 3, 2026, 10:41 a.m.
Created at: April 9, 2026, 9:32 p.m.