Triple

T12474736
Position Surface form Disambiguated ID Type / Status
Subject UnionPay E298146 entity
Predicate alsoKnownAs P39 FINISHED
Object China UnionPay E298146 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: China UnionPay | Statement: [UnionPay, alsoKnownAs, China UnionPay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: China UnionPay
Context triple: [UnionPay, alsoKnownAs, China UnionPay]
  • A. UnionPay chosen
    UnionPay is a Chinese state-backed financial services corporation best known for operating one of the world’s largest bank card and payment networks.
  • B. Ping An Bank
    Ping An Bank is a major Chinese commercial bank affiliated with the Ping An Insurance Group, offering a wide range of retail and corporate banking services.
  • C. JCB
    JCB is a major British multinational manufacturer of construction, agricultural, and industrial equipment, best known for its yellow diggers and backhoe loaders.
  • D. Huabei Bank
    Huabei Bank was a major regional Chinese bank that operated before being reorganized into the national central bank system that became the People's Bank of China.
  • E. China Merchants Bank
    China Merchants Bank is one of China’s leading commercial banks, known for its nationwide retail and corporate banking services and its headquarters in Shenzhen.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcb194c81908b5e0320ddfd463c completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f25462881908dccb831b474875d completed May 2, 2026, 6:15 p.m.
Created at: April 8, 2026, 9:56 p.m.