Triple

T19092273
Position Surface form Disambiguated ID Type / Status
Subject Lin Gengxin E467316 entity
Predicate givenName P17 FINISHED
Object Gengxin
Gengxin is a Chinese given name most notably borne by actor Lin Gengxin, known for his roles in popular Chinese films and television dramas.
 E1358030 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: Gengxin | Statement: [Lin Gengxin, givenName, Gengxin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gengxin
Context triple: [Lin Gengxin, givenName, Gengxin]
  • A. Xianheng
    Xianheng was a Chinese imperial era name used during the reign of Emperor Gaozong of the Tang dynasty.
  • B. Shengzhi
    Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
  • C. Yongrong
    Yongrong was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor and a member of the high Manchu nobility.
  • D. Jingyu
    Jingyu is a Chinese given name that can be used for people of any gender and carries various meanings depending on the characters used to write it.
  • E. Gongdi
    Gongdi is the posthumous temple name of Emperor Gong of the Sui dynasty, a short-reigning Chinese emperor during the dynasty’s final decline.
  • 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: Gengxin
Triple: [Lin Gengxin, givenName, Gengxin]
Generated description
Gengxin is a Chinese given name most notably borne by actor Lin Gengxin, known for his roles in popular Chinese films and television dramas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gengxin
Target entity description: Gengxin is a Chinese given name most notably borne by actor Lin Gengxin, known for his roles in popular Chinese films and television dramas.
  • A. Xianheng
    Xianheng was a Chinese imperial era name used during the reign of Emperor Gaozong of the Tang dynasty.
  • B. Shengzhi
    Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
  • C. Yongrong
    Yongrong was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor and a member of the high Manchu nobility.
  • D. Jingyu
    Jingyu is a Chinese given name that can be used for people of any gender and carries various meanings depending on the characters used to write it.
  • E. Gongdi
    Gongdi is the posthumous temple name of Emperor Gong of the Sui dynasty, a short-reigning Chinese emperor during the dynasty’s final decline.
  • 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_69d8dd05ac4c8190b1967d8f97f3fb2f completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e34c22a08190bf34f92f727268c5 completed April 20, 2026, 8:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05dd94ce2881909c7487971ddfe44d completed May 14, 2026, 2:35 p.m.
NEDg Description generation batch_6a05e0c9bf4c8190b748a768198d09d1 completed May 14, 2026, 2:48 p.m.
NED2 Entity disambiguation (via description) batch_6a05e147a9848190a3d0503fad7354b9 completed May 14, 2026, 2:50 p.m.
Created at: April 10, 2026, 12:04 p.m.