Triple

T740879
Position Surface form Disambiguated ID Type / Status
Subject Director General of WIPO E15239 entity
Predicate officeHolder P537 FINISHED
Object Daren Tang
Daren Tang is a Singaporean lawyer and intellectual property expert who serves as the Director General of the World Intellectual Property Organization (WIPO).
 E102658 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: Daren Tang | Statement: [Director General of WIPO, officeHolder, Daren Tang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Daren Tang
Context triple: [Director General of WIPO, officeHolder, Daren Tang]
  • A. Kenneth Hsu
    Kenneth Hsu is a Swiss geologist and oceanographer known for his influential work on marine geology and the Messinian salinity crisis.
  • B. John Cheng
    John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
  • C. Victor Wong
    Victor Wong was an American character actor known for his distinctive presence in films such as "The Last Emperor," "Big Trouble in Little China," and "Tremors."
  • D. Michael Chan
    Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
  • E. Gerald Chan
    Gerald Chan is a Hong Kong-born American billionaire investor and philanthropist known for major donations to Harvard University and leadership of the Morningside Group.
  • 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: Daren Tang
Triple: [Director General of WIPO, officeHolder, Daren Tang]
Generated description
Daren Tang is a Singaporean lawyer and intellectual property expert who serves as the Director General of the World Intellectual Property Organization (WIPO).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Daren Tang
Target entity description: Daren Tang is a Singaporean lawyer and intellectual property expert who serves as the Director General of the World Intellectual Property Organization (WIPO).
  • A. Kenneth Hsu
    Kenneth Hsu is a Swiss geologist and oceanographer known for his influential work on marine geology and the Messinian salinity crisis.
  • B. John Cheng
    John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
  • C. Victor Wong
    Victor Wong was an American character actor known for his distinctive presence in films such as "The Last Emperor," "Big Trouble in Little China," and "Tremors."
  • D. Michael Chan
    Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
  • E. Gerald Chan
    Gerald Chan is a Hong Kong-born American billionaire investor and philanthropist known for major donations to Harvard University and leadership of the Morningside Group.
  • 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_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5f4ccb48190a4eb8679a59d8e24 completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3aacc788190b79623c86b2a5fe7 completed March 4, 2026, 3:14 a.m.
NEDg Description generation batch_69a7a5f0f5e08190b6eed2d8ca594cea completed March 4, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_69a7a64ee7e08190907a9e28994cc4d2 completed March 4, 2026, 3:26 a.m.
Created at: March 1, 2026, 7:37 p.m.