Triple

T13319984
Position Surface form Disambiguated ID Type / Status
Subject Lisa Su E317289 entity
Predicate birthName P65 FINISHED
Object Su Zifeng
Su Zifeng is the birth name of Lisa Su, the Taiwanese-American electrical engineer and business executive who is the CEO of Advanced Micro Devices (AMD).
 E1043445 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: Su Zifeng | Statement: [Lisa Su, birthName, Su Zifeng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Su Zifeng
Context triple: [Lisa Su, birthName, Su Zifeng]
  • A. Chi Yufeng
    Chi Yufeng is a Chinese entrepreneur best known as the founder of the entertainment and gaming company Perfect World Co., Ltd.
  • B. Xie Feng
    Xie Feng is a Chinese diplomat who serves as the People's Republic of China’s ambassador to the United States, playing a key role in managing Sino–U.S. relations.
  • C. Xie Fei
    Xie Fei was a Chinese revolutionary and political figure best known as the wife of former PRC President Liu Shaoqi.
  • D. Zeng Fanzhi
    Zeng Fanzhi is a prominent contemporary Chinese painter best known for his emotionally charged, expressionistic works such as the "Hospital" and "Mask" series.
  • E. Nie Fengzhi
    Nie Fengzhi was a Chinese military officer and general who rose to prominence in the 20th century after receiving formal training at the Yunnan Military Academy.
  • 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: Su Zifeng
Triple: [Lisa Su, birthName, Su Zifeng]
Generated description
Su Zifeng is the birth name of Lisa Su, the Taiwanese-American electrical engineer and business executive who is the CEO of Advanced Micro Devices (AMD).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Su Zifeng
Target entity description: Su Zifeng is the birth name of Lisa Su, the Taiwanese-American electrical engineer and business executive who is the CEO of Advanced Micro Devices (AMD).
  • A. Chi Yufeng
    Chi Yufeng is a Chinese entrepreneur best known as the founder of the entertainment and gaming company Perfect World Co., Ltd.
  • B. Xie Feng
    Xie Feng is a Chinese diplomat who serves as the People's Republic of China’s ambassador to the United States, playing a key role in managing Sino–U.S. relations.
  • C. Xie Fei
    Xie Fei was a Chinese revolutionary and political figure best known as the wife of former PRC President Liu Shaoqi.
  • D. Zeng Fanzhi
    Zeng Fanzhi is a prominent contemporary Chinese painter best known for his emotionally charged, expressionistic works such as the "Hospital" and "Mask" series.
  • E. Nie Fengzhi
    Nie Fengzhi was a Chinese military officer and general who rose to prominence in the 20th century after receiving formal training at the Yunnan Military Academy.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990faa95481908a7fd297959c062e completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f74612bab88190bf1a895b87be12c1 completed May 3, 2026, 12:56 p.m.
NEDg Description generation batch_69f74eab5c9c8190b61cba7c8c965530 completed May 3, 2026, 1:33 p.m.
NED2 Entity disambiguation (via description) batch_69f74efacfc481908a0233fb824b88d5 completed May 3, 2026, 1:34 p.m.
Created at: April 9, 2026, 9:29 p.m.