Triple

T256002
Position Surface form Disambiguated ID Type / Status
Subject Battle of Hong Kong E5438 entity
Predicate location P40 FINISHED
Object Hong Kong E8492 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: Hong Kong | Statement: [Battle of Hong Kong, location, Hong Kong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hong Kong
Context triple: [Battle of Hong Kong, location, Hong Kong]
  • A. Hong Kong, China chosen
    Hong Kong, China is a major global financial and trading hub and a Special Administrative Region of China located on the southern coast of the country.
  • B. Macau
    Macau is a Special Administrative Region of China known for its blend of Portuguese and Chinese cultures and its major casino and tourism industry.
  • C. Taipei, Taiwan
    Taipei, Taiwan is the capital and largest city of Taiwan, known as a major political, economic, and cultural center in East Asia.
  • D. Shanghai
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • E. Singapore
    Singapore is a sovereign city-state and island nation in Southeast Asia known for its global financial hub status, multicultural society, and highly developed, efficient infrastructure.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d5669008190978bbd7308be11f7 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a37958242c81909d114fba70b4211c completed Feb. 28, 2026, 11:25 p.m.
Created at: Feb. 28, 2026, 2:55 a.m.