Triple

T8045769
Position Surface form Disambiguated ID Type / Status
Subject Sima Guang E187546 entity
Predicate familyName P18 FINISHED
Object Sima
Sima is a Chinese surname historically associated with prominent figures such as the Song dynasty historian and statesman Sima Guang.
 E706369 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: Sima | Statement: [Sima Guang, familyName, Sima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sima
Context triple: [Sima Guang, familyName, Sima]
  • A. Sima Samar
    Sima Samar is an Afghan physician and human rights advocate renowned for her work promoting women's rights, education, and social justice in Afghanistan.
  • B. Sicong
    Sicong is a given name most notably associated with Ma Sicong, a prominent 20th-century Chinese composer and violinist.
  • C. Ganlu
    Ganlu was a historical Chinese era name used during the Cao Wei state of the Three Kingdoms period.
  • D. Taishi
    Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
  • E. Cai
    Cai is a common Chinese surname shared by numerous individuals, including the contemporary artist Cai Guo-Qiang.
  • 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: Sima
Triple: [Sima Guang, familyName, Sima]
Generated description
Sima is a Chinese surname historically associated with prominent figures such as the Song dynasty historian and statesman Sima Guang.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sima
Target entity description: Sima is a Chinese surname historically associated with prominent figures such as the Song dynasty historian and statesman Sima Guang.
  • A. Sima Samar
    Sima Samar is an Afghan physician and human rights advocate renowned for her work promoting women's rights, education, and social justice in Afghanistan.
  • B. Sicong
    Sicong is a given name most notably associated with Ma Sicong, a prominent 20th-century Chinese composer and violinist.
  • C. Ganlu
    Ganlu was a historical Chinese era name used during the Cao Wei state of the Three Kingdoms period.
  • D. Taishi
    Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
  • E. Cai
    Cai is a common Chinese surname shared by numerous individuals, including the contemporary artist Cai Guo-Qiang.
  • 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_69cc5711d2bc8190911f2cade7596be5 completed March 31, 2026, 11:21 p.m.
NEDg Description generation batch_69cc58edb31881909b6efd2fbbc2480e completed March 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_69cc5ccee5648190a8ebdf8029eded98 completed March 31, 2026, 11:46 p.m.
Created at: March 30, 2026, 5:24 p.m.