Triple

T468101
Position Surface form Disambiguated ID Type / Status
Subject Hong Kong E8492 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object HK 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: HK | Statement: [Hong Kong, vehicleRegistrationCode, HK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HK
Context triple: [Hong Kong, vehicleRegistrationCode, HK]
  • 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. Hakka
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • C. 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.
  • 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. Lingnan
    Lingnan is a historic cultural and geographic region of southern China, centered on modern Guangdong and Guangxi, known for its distinct Cantonese language, cuisine, and traditions.
  • 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_69a2e7f3aeb48190a19453e3a043f486 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efd9bea081909ee782840f3da12b completed Feb. 28, 2026, 1:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69a467fd7cc48190b00982c4f1c41eaf completed March 1, 2026, 4:23 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.