Triple

T449346
Position Surface form Disambiguated ID Type / Status
Subject Macau E7092 entity
Predicate largestCity P235 FINISHED
Object Macau E7092 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: Macau | Statement: [Macau, largestCity, Macau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macau
Context triple: [Macau, largestCity, 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. 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.
  • C. Pearl River Delta
    The Pearl River Delta is a highly urbanized and economically vital megaregion in southern China, encompassing major cities such as Guangzhou, Shenzhen, and Hong Kong.
  • D. Kwang-Chou-Wan
    Kwang-Chou-Wan was a small leased territory in southern China that served as a French colonial enclave administered as part of French Indochina in the late 19th and early 20th centuries.
  • E. 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.
  • 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_69a2e7e4676c81909ea0dbdecac0687c completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ef6755a08190a057e72279b70456 completed Feb. 28, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69a46c5a949081908e05f0b61795004f completed March 1, 2026, 4:42 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.