Triple

T17742302
Position Surface form Disambiguated ID Type / Status
Subject Zhujiang E442890 entity
Predicate majorCityOnRiver P316 FINISHED
Object Macau 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: Macau | Statement: [Zhujiang, majorCityOnRiver, Macau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macau
Context triple: [Zhujiang, majorCityOnRiver, Macau]
  • A. Macau chosen
    Macau is a Special Administrative Region of China known for its blend of Portuguese and Chinese cultures and its major casino and tourism industry.
  • B. Macau
    Macau is a coastal municipality in the Brazilian state of Rio Grande do Norte, known for its salt production and fishing activities.
  • C. Magong
    Magong is the main urban center and largest city of Taiwan’s Penghu (Pescadores) archipelago, serving as its political, economic, and transportation hub.
  • D. Hong Kong, China
    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.
  • E. 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.
  • 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e47ace58988190b927ca29af7a8b77 completed April 19, 2026, 6:48 a.m.
Created at: April 10, 2026, 10:09 a.m.