Triple

T15516373
Position Surface form Disambiguated ID Type / Status
Subject Peng-Peng Lee E368843 entity
Predicate givenName P17 FINISHED
Object Peng-Yen
Peng-Yen is the given name of Peng-Peng Lee, a Canadian artistic gymnast known for her NCAA career with the UCLA Bruins and international competition for Canada.
E1164320 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: Peng-Yen | Statement: [Peng-Peng Lee, givenName, Peng-Yen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peng-Yen
Context triple: [Peng-Peng Lee, givenName, Peng-Yen]
  • A. Hung-jen
    Hung-jen, also known as Hongren, was a prominent 7th-century Chinese Chan (Zen) Buddhist master traditionally regarded as the Fifth Patriarch of Chan Buddhism.
  • B. Hsiao-wen
    Hsiao-wen is the given name of Chiang Hsiao-wen, a member of the Chiang family associated with modern Chinese political history.
  • C. Kar-ying
    Kar-ying is the given name of Law Kar-ying, a veteran Hong Kong actor and Cantonese opera performer known for his roles in film and television.
  • D. Hsiao-chang
    Hsiao-chang is a member of the Chiang family, a prominent political dynasty in modern Chinese and Taiwanese history.
  • E. Chih-chung
    Chih-chung is an alternative romanization of the Chinese given name Zhizhong, used in older or non–pinyin transcription systems.
  • 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: Peng-Yen
Triple: [Peng-Peng Lee, givenName, Peng-Yen]
Generated description
Peng-Yen is the given name of Peng-Peng Lee, a Canadian artistic gymnast known for her NCAA career with the UCLA Bruins and international competition for Canada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Peng-Yen
Target entity description: Peng-Yen is the given name of Peng-Peng Lee, a Canadian artistic gymnast known for her NCAA career with the UCLA Bruins and international competition for Canada.
  • A. Hung-jen
    Hung-jen, also known as Hongren, was a prominent 7th-century Chinese Chan (Zen) Buddhist master traditionally regarded as the Fifth Patriarch of Chan Buddhism.
  • B. Hsiao-wen
    Hsiao-wen is the given name of Chiang Hsiao-wen, a member of the Chiang family associated with modern Chinese political history.
  • C. Kar-ying
    Kar-ying is the given name of Law Kar-ying, a veteran Hong Kong actor and Cantonese opera performer known for his roles in film and television.
  • D. Hsiao-chang
    Hsiao-chang is a member of the Chiang family, a prominent political dynasty in modern Chinese and Taiwanese history.
  • E. Chih-chung
    Chih-chung is an alternative romanization of the Chinese given name Zhizhong, used in older or non–pinyin transcription systems.
  • 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_69d85a1794cc8190b0b428716296e63e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e04033303c8190a87b6384f68a6921 completed April 16, 2026, 1:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c3618dc8190aab243bb61d198ce completed May 9, 2026, 3:01 p.m.
NEDg Description generation batch_69ff4e000eb481909f1ddf7b24130c7a completed May 9, 2026, 3:08 p.m.
NED2 Entity disambiguation (via description) batch_69ff4e57445c8190969327311c73b2e6 completed May 9, 2026, 3:10 p.m.
Created at: April 10, 2026, 4:02 a.m.