Triple

T5693601
Position Surface form Disambiguated ID Type / Status
Subject The Wedding Banquet E125482 entity
Predicate mainCharacter P1183 FINISHED
Object Simon
Simon is the central character in Ang Lee's 1993 film "The Wedding Banquet," a Taiwanese American man who enters a sham marriage to appease his traditional parents while secretly living with his male partner in New York.
 E552612 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: Simon | Statement: [The Wedding Banquet, mainCharacter, Simon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Simon
Context triple: [The Wedding Banquet, mainCharacter, Simon]
  • A. Simon
    Simon is a common masculine given name of Hebrew origin, widely used in many cultures and languages.
  • B. Simon
    Simon is the given name of Simon Bolivar Buckner Jr., a U.S. Army lieutenant general who was killed in action while commanding forces during the Battle of Okinawa in World War II.
  • C. Simon
    Simon is a common surname of English and Jewish origin borne by numerous notable individuals across politics, business, arts, and sciences.
  • D. Simon
    Simon is a sleazy used-car salesman and comic-relief character in the action-comedy film "True Lies," who pretends to be a secret agent to seduce women.
  • E. Sam
    Sam is a person whose given name is Sam.
  • 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: Simon
Triple: [The Wedding Banquet, mainCharacter, Simon]
Generated description
Simon is the central character in Ang Lee's 1993 film "The Wedding Banquet," a Taiwanese American man who enters a sham marriage to appease his traditional parents while secretly living with his male partner in New York.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Simon
Target entity description: Simon is the central character in Ang Lee's 1993 film "The Wedding Banquet," a Taiwanese American man who enters a sham marriage to appease his traditional parents while secretly living with his male partner in New York.
  • A. Simon
    Simon is the given name of Simon Bolivar Buckner Jr., a U.S. Army lieutenant general who was killed in action while commanding forces during the Battle of Okinawa in World War II.
  • B. Simon
    Simon is a common surname of English and Jewish origin borne by numerous notable individuals across politics, business, arts, and sciences.
  • C. Simon
    Simon is a sleazy used-car salesman and comic-relief character in the action-comedy film "True Lies," who pretends to be a secret agent to seduce women.
  • D. Simon
    Simon is a common masculine given name of Hebrew origin, widely used in many cultures and languages.
  • E. Sam
    Sam is a person whose given name is Sam.
  • 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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023e7dbe48190850b501f223614e3 completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0ade6648190b29c64f83ceed326 completed March 23, 2026, 3:17 a.m.
NEDg Description generation batch_69c0b1c9ebdc819089752d150b584a6f completed March 23, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_69c0b27981848190a5b7c618044241b0 completed March 23, 2026, 3:24 a.m.
Created at: March 22, 2026, 3:44 p.m.