Triple

T16731399
Position Surface form Disambiguated ID Type / Status
Subject Yongqi E406600 entity
Predicate givenName P17 FINISHED
Object Yongqi E406600 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: Yongqi | Statement: [Yongqi, givenName, Yongqi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yongqi
Context triple: [Yongqi, givenName, Yongqi]
  • A. Yongqi chosen
    Yongqi was a Qing dynasty imperial prince, noted as one of the most talented sons of the Qianlong Emperor before his early death.
  • B. Wuling
    Wuling is the historical name of a region in Hunan, China, that later became known as Changde.
  • C. Wuling
    Wuling is a Chinese automotive marque known for producing affordable compact cars and microvans, marketed through a joint venture involving General Motors.
  • D. Fuxing
    Fuxing is a series of Chinese high-speed electric multiple unit trains known for their advanced technology, high operating speeds, and use on major routes across China’s high-speed rail network.
  • E. Guangqi
    Guangqi was the era name used during part of Emperor Xizong of the Tang dynasty’s reign in late ninth-century China.
  • 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e39c362bb88190921fab43d76c3ee8 completed April 18, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d4a94688190aabe56c34e8cc2c3 completed May 10, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:20 a.m.