Triple

T16247639
Position Surface form Disambiguated ID Type / Status
Subject Bus Stop (play) E394414 entity
Predicate hasMainCharacter P1183 FINISHED
Object Carl
Carl is the central character in the play "Bus Stop," around whom much of the story’s interpersonal drama and development revolves.
E1201791 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: Carl | Statement: [Bus Stop (play), hasMainCharacter, Carl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carl
Context triple: [Bus Stop (play), hasMainCharacter, Carl]
  • A. Carl
    Carl is the given name of Carl Sagan, the renowned American astronomer, science communicator, and author.
  • B. Carl
    Carl is the given name of the influential American microbiologist Carl Woese, known for defining the Archaea domain of life.
  • C. Carl
    Carl is the given name of Carl Schorske, a prominent American cultural and intellectual historian known for his influential work on fin-de-siècle Vienna.
  • D. Carl
    Carl is the given name of Carl von Martius, a notable 19th-century German botanist and explorer known for his extensive studies of Brazilian flora.
  • E. Carl
    Carl is the given name of the German Romantic composer and conductor Carl Maria von Weber, known for works such as the opera "Der Freischütz."
  • 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: Carl
Triple: [Bus Stop (play), hasMainCharacter, Carl]
Generated description
Carl is the central character in the play "Bus Stop," around whom much of the story’s interpersonal drama and development revolves.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Carl
Target entity description: Carl is the central character in the play "Bus Stop," around whom much of the story’s interpersonal drama and development revolves.
  • A. Carl
    Carl is a supporting character in the classic film "Casablanca," working at Rick Blaine's nightclub, Rick's Café Américain.
  • B. Carl
    Carl is the abusive father of Claireece "Precious" Jones in the novel and film "Precious," central to the story's depiction of trauma and hardship.
  • C. Carl
    Carl is the protagonist of the psychological horror video game "The Coma," navigating a nightmarish version of his school while uncovering dark secrets.
  • D. Carl
    Carl is a central character in the British comedy film "The Boat That Rocked," portrayed as a young man who joins a pirate radio ship in the 1960s and comes of age amid its rebellious DJs and rock music culture.
  • E. Carl
    Carl is a supporting character in the film "Van Helsing," depicted as a witty and inventive friar who aids the titular monster hunter.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245942460819080897afad0d2fe09 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ee3bbc48190a56ce2807a9510f0 completed May 10, 2026, 4:51 a.m.
NEDg Description generation batch_6a000f9aecec819087cecb1edad6b710 completed May 10, 2026, 4:54 a.m.
NED2 Entity disambiguation (via description) batch_6a0010462ba881909666051b2fc38d43 completed May 10, 2026, 4:57 a.m.
Created at: April 10, 2026, 5:04 a.m.