Triple

T15297048
Position Surface form Disambiguated ID Type / Status
Subject Love, Wedding, Marriage E365686 entity
Predicate hasMainCharacter P1183 FINISHED
Object Charlie
Charlie is the central protagonist in the romantic film "Love, Wedding, Marriage," around whom the story’s relationship and marital themes revolve.
E1148104 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: Charlie | Statement: [Love, Wedding, Marriage, hasMainCharacter, Charlie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charlie
Context triple: [Love, Wedding, Marriage, hasMainCharacter, Charlie]
  • A. Charlie
    Charlie is a central character in the romantic comedy film "French Kiss," serving as the unfaithful fiancé whose actions set the story’s events in motion.
  • B. Charlie
    Charlie is the given name of English actor and producer Charlie Bewley, known for his role as Demetri in the Twilight film series.
  • C. Charlie
    Charlie is a fictional character from Stephen Adly Guirgis’s gritty stage play "In Arabia We’d All Be Kings," which portrays the lives of struggling New Yorkers in a rapidly gentrifying Hell’s Kitchen.
  • D. Charlie
    Charlie is a classic Revlon perfume line known for its accessible, youthful, and independent image, especially popular from the 1970s onward.
  • E. Charlie
    Charlie is the ambitious New York City hustler and small-time crook who serves as the central protagonist in the crime drama film "The Pope of Greenwich Village."
  • 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: Charlie
Triple: [Love, Wedding, Marriage, hasMainCharacter, Charlie]
Generated description
Charlie is the central protagonist in the romantic film "Love, Wedding, Marriage," around whom the story’s relationship and marital themes revolve.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Charlie
Target entity description: Charlie is the central protagonist in the romantic film "Love, Wedding, Marriage," around whom the story’s relationship and marital themes revolve.
  • A. Charlie
    Charlie is a central character in the romantic comedy film "French Kiss," serving as the unfaithful fiancé whose actions set the story’s events in motion.
  • B. Charlie
    Charlie is the protagonist of the 1987 film "Happy New Year," around whom the movie’s central story and character development revolve.
  • C. Charlie
    Charlie is a character featured in the work titled "Seascape."
  • D. Charlie
    Charlie is the central protagonist of the apocalyptic horror film "Legion" (2010), a pregnant waitress whose unborn child is believed to be humanity’s last hope.
  • E. Charlie
    Charlie is a person whose full name is Charlie Watson.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e036848c1881908fbaaae0216d6d27 completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feef82f6d08190b809260dda247dfe completed May 9, 2026, 8:25 a.m.
NEDg Description generation batch_69fef08efec88190a66159ba39409ec9 completed May 9, 2026, 8:30 a.m.
NED2 Entity disambiguation (via description) batch_69fef1715c3081909bddb24688c810a7 completed May 9, 2026, 8:33 a.m.
Created at: April 10, 2026, 3:15 a.m.