Triple

T1821965
Position Surface form Disambiguated ID Type / Status
Subject Markham, Ontario E40557 entity
Predicate hasSisterCity P919 FINISHED
Object Wuhan, China E1680 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: Wuhan, China | Statement: [Markham, Ontario, hasSisterCity, Wuhan, China]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wuhan, China
Context triple: [Markham, Ontario, hasSisterCity, Wuhan, China]
  • A. Wuhan chosen
    Wuhan is a major city in central China, known as a key industrial, commercial, and transportation hub located at the confluence of the Yangtze and Han rivers.
  • B. Port of Wuhan
    The Port of Wuhan is a major inland river port on the Yangtze River in central China, serving as a key hub for regional trade and transportation.
  • C. Shenzhen, China
    Shenzhen, China is a major southern Chinese metropolis known for its rapid transformation into a global technology and manufacturing hub bordering Hong Kong.
  • D. Huangshi
    Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
  • 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_69a8864526c081908a3a4d74f689e2c5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa662b910c8190b1746730ee09015a completed March 6, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf6526f88190907de68a5344a084 completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:32 p.m.