Triple

T16776589
Position Surface form Disambiguated ID Type / Status
Subject Empress Dowager Xiaoding E407739 entity
Predicate posthumousName P744 FINISHED
Object Xiaoding
Xiaoding is the posthumous honorific title of Empress Dowager Xiaoding, a high-ranking imperial consort and mother of an emperor in Chinese history.
E1233175 NE FINISHED

How this triple was built (4 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: Xiaoding | Statement: [Empress Dowager Xiaoding, posthumousName, Xiaoding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xiaoding
Context triple: [Empress Dowager Xiaoding, posthumousName, Xiaoding]
  • A. Xiaode
    Xiaode was the posthumous honorific title granted to Empress Fang of the Ming dynasty, reflecting her perceived virtue and moral excellence.
  • B. Xiaoyeliu
    Xiaoyeliu is a coastal geological area in eastern Taiwan known for its striking wave-eroded rock formations and scenic seaside landscapes.
  • C. Xiaobo
    Xiaobo is the given name of Liu Xiaobo, the Chinese literary critic, human rights activist, and Nobel Peace Prize laureate.
  • D. Xiao Hua
    Xiao Hua is best known as the former wife of acclaimed Chinese film director Zhang Yimou.
  • E. Xiaozong
    Xiaozong is the temple name of the Hongzhi Emperor, a Ming dynasty ruler noted for his relatively peaceful and reform-minded reign in late 15th-century China.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Xiaoding
Triple: [Empress Dowager Xiaoding, posthumousName, Xiaoding]
Generated description
Xiaoding is the posthumous honorific title of Empress Dowager Xiaoding, a high-ranking imperial consort and mother of an emperor in Chinese history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Xiaoding
Target entity description: Xiaoding is the posthumous honorific title of Empress Dowager Xiaoding, a high-ranking imperial consort and mother of an emperor in Chinese history.
  • A. Xiaode
    Xiaode was the posthumous honorific title granted to Empress Fang of the Ming dynasty, reflecting her perceived virtue and moral excellence.
  • B. Xiaoyeliu
    Xiaoyeliu is a coastal geological area in eastern Taiwan known for its striking wave-eroded rock formations and scenic seaside landscapes.
  • C. Xiaobo
    Xiaobo is the given name of Liu Xiaobo, the Chinese literary critic, human rights activist, and Nobel Peace Prize laureate.
  • D. Xiao Hua
    Xiao Hua is best known as the former wife of acclaimed Chinese film director Zhang Yimou.
  • E. Xiaozong
    Xiaozong is the temple name of the Hongzhi Emperor, a Ming dynasty ruler noted for his relatively peaceful and reform-minded reign in late 15th-century China.
  • F. None of above. chosen

Provenance (5 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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b03a646c8190b3944c9f0c25af27 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aafe1f8081909b9540aca6e7b9b7 completed May 10, 2026, 3:57 p.m.
NEDg Description generation batch_6a00ac0e10648190803bf962a4677104 completed May 10, 2026, 4:02 p.m.
NED2 Entity disambiguation (via description) batch_6a00acc658f881908db64ebfa5a86f84 completed May 10, 2026, 4:05 p.m.
Created at: April 10, 2026, 5:22 a.m.