Triple

T8045768
Position Surface form Disambiguated ID Type / Status
Subject Sima Guang E187546 entity
Predicate givenName P17 FINISHED
Object Guang
Guang is the given name of Sima Guang, a renowned Song dynasty historian, scholar, and high-ranking official in imperial China.
 E713347 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: Guang | Statement: [Sima Guang, givenName, Guang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Guang
Context triple: [Sima Guang, givenName, Guang]
  • A. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • B. Guangyi
    Guangyi was a warship that served in China's late 19th-century Beiyang Fleet, one of the Qing dynasty's principal modern naval forces.
  • C. Guangjia
    Guangjia was a warship of China’s late 19th-century Beiyang Fleet, one of the Qing dynasty’s principal modern naval forces.
  • D. Hui
    The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
  • E. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • 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: Guang
Triple: [Sima Guang, givenName, Guang]
Generated description
Guang is the given name of Sima Guang, a renowned Song dynasty historian, scholar, and high-ranking official in imperial China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Guang
Target entity description: Guang is the given name of Sima Guang, a renowned Song dynasty historian, scholar, and high-ranking official in imperial China.
  • A. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • B. Guangyi
    Guangyi was a warship that served in China's late 19th-century Beiyang Fleet, one of the Qing dynasty's principal modern naval forces.
  • C. Guangjia
    Guangjia was a warship of China’s late 19th-century Beiyang Fleet, one of the Qing dynasty’s principal modern naval forces.
  • D. Hui
    The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
  • E. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • 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_69ca82b00cb48190b59a300f70e97bd7 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f4d9ddc8190a7dcf85ed47ee6c3 completed March 31, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc93c407cc81908029bfdd5a0393f1 completed April 1, 2026, 3:40 a.m.
NEDg Description generation batch_69cc9557c6148190a759021b6add0a61 completed April 1, 2026, 3:47 a.m.
NED2 Entity disambiguation (via description) batch_69cc96a8bb688190a352de1798b380f1 completed April 1, 2026, 3:53 a.m.
Created at: March 30, 2026, 5:24 p.m.