Triple

T13403375
Position Surface form Disambiguated ID Type / Status
Subject Peng Chau E319889 entity
Predicate locatedIn P40 FINISHED
Object Hong Kong SAR 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 SAR | Statement: [Peng Chau, locatedIn, Hong Kong SAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hong Kong SAR
Context triple: [Peng Chau, locatedIn, Hong Kong SAR]
  • 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. 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.
  • D. Macau
    Macau is a coastal municipality in the Brazilian state of Rio Grande do Norte, known for its salt production and fishing activities.
  • E. Kowloon
    Kowloon is a densely populated urban area of Hong Kong known for its vibrant street life, markets, and skyline facing Victoria Harbour.
  • 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbae4ae47081909b68a9aaa62fd4c7 completed April 12, 2026, 2:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe249a972081909b30302865396eb1 completed May 8, 2026, 5:59 p.m.
Created at: April 9, 2026, 9:34 p.m.