Triple

T11902773
Position Surface form Disambiguated ID Type / Status
Subject Peng Yuchang E283195 entity
Predicate nativeName P15 FINISHED
Object 彭昱畅
彭昱畅是一位中国内地男演员,以在青春片和喜剧作品中的自然演技和亲和力而受到广泛关注。
E953767 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: 彭昱畅 | Statement: [Peng Yuchang, nativeName, 彭昱畅]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 彭昱畅
Context triple: [Peng Yuchang, nativeName, 彭昱畅]
  • A. Yuan Xiaoyuan
    Yuan Xiaoyuan was a pioneering Chinese female diplomat and politician, recognized as one of the earliest women to serve in China’s foreign service.
  • B. Kris Wu
    Kris Wu is a Chinese-Canadian singer, rapper, actor, and former member of the K-pop group EXO who later pursued a solo entertainment career in China and internationally.
  • C. Chen Yifei
    Chen Yifei was a prominent Chinese painter and film director known for his romantic realist style and influential role in modern Chinese art.
  • D. Lu Han
    Lu Han was a prominent Chinese Nationalist general and warlord who controlled Yunnan province during the Republican era and played a key role in the Second Sino-Japanese War.
  • E. Peng Yuxing
    Peng Yuxing is a Chinese chemist and former provincial science and technology official who became known for his role in Sichuan’s scientific development and subsequent investigation on corruption charges.
  • 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: 彭昱畅
Triple: [Peng Yuchang, nativeName, 彭昱畅]
Generated description
彭昱畅是一位中国内地男演员,以在青春片和喜剧作品中的自然演技和亲和力而受到广泛关注。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 彭昱畅
Target entity description: 彭昱畅是一位中国内地男演员,以在青春片和喜剧作品中的自然演技和亲和力而受到广泛关注。
  • A. Yuan Xiaoyuan
    Yuan Xiaoyuan was a pioneering Chinese female diplomat and politician, recognized as one of the earliest women to serve in China’s foreign service.
  • B. Kris Wu
    Kris Wu is a Chinese-Canadian singer, rapper, actor, and former member of the K-pop group EXO who later pursued a solo entertainment career in China and internationally.
  • C. Chen Yifei
    Chen Yifei was a prominent Chinese painter and film director known for his romantic realist style and influential role in modern Chinese art.
  • D. Lu Han
    Lu Han was a prominent Chinese Nationalist general and warlord who controlled Yunnan province during the Republican era and played a key role in the Second Sino-Japanese War.
  • E. Peng Yuxing
    Peng Yuxing is a Chinese chemist and former provincial science and technology official who became known for his role in Sichuan’s scientific development and subsequent investigation on corruption charges.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1792648190853f15fbf217eebd completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4183d29b081908cfbf4d91a365681 completed May 1, 2026, 3:04 a.m.
NEDg Description generation batch_69f41f1d2da0819082f00cf61a6530b6 completed May 1, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f4228a73708190a6d2db321e175921 completed May 1, 2026, 3:48 a.m.
Created at: April 8, 2026, 9:44 p.m.