Triple

T17180043
Position Surface form Disambiguated ID Type / Status
Subject Wang Da-hong E416957 entity
Predicate name P16 FINISHED
Object Wang Da-hong NE ONNED1

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: Wang Da-hong | Statement: [Wang Da-hong, name, Wang Da-hong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wang Da-hong
Context triple: [Wang Da-hong, name, Wang Da-hong]
  • A. Wang Da-hong chosen
    Wang Da-hong was a prominent Chinese-Taiwanese modernist architect known for blending Western modernism with traditional Chinese elements in landmark buildings across Taiwan.
  • B. Ma Hongkui
    Ma Hongkui was a prominent Chinese Muslim warlord and Kuomintang general who controlled Ningxia during the Republic of China era.
  • C. Lai Wenguang
    Lai Wenguang was a prominent Qing-dynasty Chinese rebel general best known for his leading role in the mid-19th century Nian Rebellion against imperial rule.
  • D. Wang Xiancheng
    Wang Xiancheng was a Ming dynasty official and scholar best known for creating the renowned classical Chinese landscape garden now called the Humble Administrator's Garden in Suzhou.
  • E. Wang Hongwei
    Wang Hongwei is a Chinese actor best known for his frequent collaborations with director Jia Zhangke in acclaimed independent films.
  • 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3fc10afb48190a71f4a46f0280a14 completed April 18, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0195443f54819098130cf593eb56cb in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:37 a.m.