Triple

T8385001
Position Surface form Disambiguated ID Type / Status
Subject Infernal Affairs E197793 entity
Predicate editor P1954 FINISHED
Object Curran Pang
Curran Pang is a film editor best known for his work on the acclaimed Hong Kong crime thriller "Infernal Affairs."
 E731780 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: Curran Pang | Statement: [Infernal Affairs, editor, Curran Pang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Curran Pang
Context triple: [Infernal Affairs, editor, Curran Pang]
  • A. Topher Ngo
    Topher Ngo is a voice actor and singer best known for his role in Pixar's animated film "Turning Red."
  • B. Felix Chong
    Felix Chong is a Hong Kong filmmaker best known as the co-writer and co-creator of the acclaimed crime thriller series "Infernal Affairs," which inspired Martin Scorsese’s "The Departed."
  • C. Christopher Chung
    Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
  • D. David Luan
    David Luan is an AI researcher and entrepreneur known for his work on large language models at OpenAI and as co-founder and CEO of Adept AI.
  • E. Crispin Sorhaindo
    Crispin Sorhaindo was a Dominican politician who served as President of the Commonwealth of Dominica in the 1990s.
  • 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: Curran Pang
Triple: [Infernal Affairs, editor, Curran Pang]
Generated description
Curran Pang is a film editor best known for his work on the acclaimed Hong Kong crime thriller "Infernal Affairs."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Curran Pang
Target entity description: Curran Pang is a film editor best known for his work on the acclaimed Hong Kong crime thriller "Infernal Affairs."
  • A. Topher Ngo
    Topher Ngo is a voice actor and singer best known for his role in Pixar's animated film "Turning Red."
  • B. Felix Chong
    Felix Chong is a Hong Kong filmmaker best known as the co-writer and co-creator of the acclaimed crime thriller series "Infernal Affairs," which inspired Martin Scorsese’s "The Departed."
  • C. Christopher Chung
    Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
  • D. David Luan
    David Luan is an AI researcher and entrepreneur known for his work on large language models at OpenAI and as co-founder and CEO of Adept AI.
  • E. Crispin Sorhaindo
    Crispin Sorhaindo was a Dominican politician who served as President of the Commonwealth of Dominica in the 1990s.
  • 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_69ca82f749388190bffbea6dfb509016 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80e03eb08190a458c9caa0524e0f completed March 31, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce02c0664481908f3c79246350a248 completed April 2, 2026, 5:46 a.m.
NEDg Description generation batch_69ce064211e48190b558d4355be659ba completed April 2, 2026, 6:01 a.m.
NED2 Entity disambiguation (via description) batch_69ce07a390048190ac26a7e3d3d561e0 completed April 2, 2026, 6:07 a.m.
Created at: March 30, 2026, 6:02 p.m.