Triple

T3949832
Position Surface form Disambiguated ID Type / Status
Subject The Mysterious Mr. Wong E84836 entity
Predicate hasVillain P32100 FINISHED
Object Mr. Wong
Mr. Wong is the enigmatic criminal mastermind and primary antagonist in the 1934 mystery film "The Mysterious Mr. Wong."
 E403202 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: Mr. Wong | Statement: [The Mysterious Mr. Wong, hasVillain, Mr. Wong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mr. Wong
Context triple: [The Mysterious Mr. Wong, hasVillain, Mr. Wong]
  • A. Jimmy Woo
    Jimmy Woo is a Marvel Comics and Marvel Cinematic Universe character, depicted as an earnest and by-the-book FBI agent who often becomes entangled in superhero-related investigations.
  • B. Mr. Wuf
    Mr. Wuf is the costumed wolf mascot who represents North Carolina State University's athletic teams and school spirit.
  • C. Charlie Lucky
    Charlie Lucky is an alias of Lucky Luciano, the influential Italian-American mobster considered a founding figure of modern organized crime in the United States.
  • D. Wong
    Wong is a common Chinese surname shared by many people of Chinese descent worldwide.
  • E. Mr. Chow
    Mr. Chow is a flamboyant, unpredictable, and often outrageous criminal associate who provides much of the chaotic comic relief in The Hangover film series.
  • 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: Mr. Wong
Triple: [The Mysterious Mr. Wong, hasVillain, Mr. Wong]
Generated description
Mr. Wong is the enigmatic criminal mastermind and primary antagonist in the 1934 mystery film "The Mysterious Mr. Wong."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mr. Wong
Target entity description: Mr. Wong is the enigmatic criminal mastermind and primary antagonist in the 1934 mystery film "The Mysterious Mr. Wong."
  • A. Jimmy Woo
    Jimmy Woo is a Marvel Comics and Marvel Cinematic Universe character, depicted as an earnest and by-the-book FBI agent who often becomes entangled in superhero-related investigations.
  • B. Mr. Wuf
    Mr. Wuf is the costumed wolf mascot who represents North Carolina State University's athletic teams and school spirit.
  • C. Charlie Lucky
    Charlie Lucky is an alias of Lucky Luciano, the influential Italian-American mobster considered a founding figure of modern organized crime in the United States.
  • D. Wong
    Wong is a common Chinese surname shared by many people of Chinese descent worldwide.
  • E. Mr. Chow
    Mr. Chow is a flamboyant, unpredictable, and often outrageous criminal associate who provides much of the chaotic comic relief in The Hangover film series.
  • 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_69aed934fbfc8190847068e4546de963 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef91227a8819097c3a5a206792382 completed March 9, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b53ffc49f48190949d14113031dd85 completed March 14, 2026, 11:01 a.m.
NEDg Description generation batch_69b54111e5188190ab8ec23124c22981 completed March 14, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69b54193105c81909e2a4e368aae36e8 completed March 14, 2026, 11:08 a.m.
Created at: March 9, 2026, 3:30 p.m.