Triple

T17024293
Position Surface form Disambiguated ID Type / Status
Subject Police Story E413023 entity
Predicate writtenBy P806 FINISHED
Object Edward Tang
Edward Tang is a Hong Kong screenwriter best known for his work on Jackie Chan–led action films, including the influential "Police Story" series.
E1251019 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: Edward Tang | Statement: [Police Story, writtenBy, Edward Tang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edward Tang
Context triple: [Police Story, writtenBy, Edward Tang]
  • A. 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).
  • B. Edward Wang
    Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
  • C. Stephen Wang
    Stephen Wang is an entrepreneur best known as a co-founder of the film and television review aggregation website Rotten Tomatoes.
  • D. Charles Huang
    Charles Huang is an American entrepreneur best known as the co-founder of RedOctane, the company behind the hit video game franchise Guitar Hero.
  • E. 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."
  • 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: Edward Tang
Triple: [Police Story, writtenBy, Edward Tang]
Generated description
Edward Tang is a Hong Kong screenwriter best known for his work on Jackie Chan–led action films, including the influential "Police Story" series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Edward Tang
Target entity description: Edward Tang is a Hong Kong screenwriter best known for his work on Jackie Chan–led action films, including the influential "Police Story" series.
  • A. 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).
  • B. Edward Wang
    Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
  • C. Stephen Wang
    Stephen Wang is an entrepreneur best known as a co-founder of the film and television review aggregation website Rotten Tomatoes.
  • D. Charles Huang
    Charles Huang is an American entrepreneur best known as the co-founder of RedOctane, the company behind the hit video game franchise Guitar Hero.
  • E. 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."
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d371148190a60d32a72abec09a completed April 18, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139ef70208190b26029511e91afb0 completed May 11, 2026, 2:07 a.m.
NEDg Description generation batch_6a013bd2cb708190b7e33dad9b461ae0 completed May 11, 2026, 2:15 a.m.
NED2 Entity disambiguation (via description) batch_6a013c23f8808190856afdcbf2854244 completed May 11, 2026, 2:17 a.m.
Created at: April 10, 2026, 5:33 a.m.