Triple

T18954210
Position Surface form Disambiguated ID Type / Status
Subject Pace Gallery E463729 entity
Predicate location P40 FINISHED
Object Hong Kong NE NERFINISHED

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: [Pace Gallery, location, Hong Kong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hong Kong
Context triple: [Pace Gallery, 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. China Hong Kong City
    China Hong Kong City is a large mixed-use complex in Tsim Sha Tsui, Hong Kong, featuring a ferry terminal, shopping mall, offices, and a hotel.
  • C. Kowloon
    Kowloon is a densely populated urban area of Hong Kong known for its vibrant street life, markets, and skyline facing Victoria Harbour.
  • D. 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.
  • E. Macau
    Macau is a coastal municipality in the Brazilian state of Rio Grande do Norte, known for its salt production and fishing activities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcffc278819086792a4ebfddfafa completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d545f47881909110e6a92e86b384 completed April 20, 2026, 7:27 a.m.
Created at: April 10, 2026, noon