Triple

T20248645
Position Surface form Disambiguated ID Type / Status
Subject The Whale E498490 entity
Predicate character P662 FINISHED
Object Charlie
Charlie is the morbidly obese, reclusive English teacher at the center of Darren Aronofsky’s film "The Whale," whose attempts to reconnect with his estranged daughter drive the story’s emotional core.
E1421154 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: [The Whale, character, Charlie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charlie
Context triple: [The Whale, character, Charlie]
  • A. 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."
  • B. Charlie
    Charlie is a fictional character portrayed by American actor Jared Rushton, best known for his roles in late-1980s films.
  • C. Charlie
    Charlie is a person whose full name is Charlie Watson.
  • D. Charlie
    Charlie is the central protagonist in the romantic film "Love, Wedding, Marriage," around whom the story’s relationship and marital themes revolve.
  • E. Charlie
    Charlie is a fictional character who serves as the central figure in the story "The Winner."
  • 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: [The Whale, character, Charlie]
Generated description
Charlie is the morbidly obese, reclusive English teacher at the center of Darren Aronofsky’s film "The Whale," whose attempts to reconnect with his estranged daughter drive the story’s emotional core.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Charlie
Target entity description: Charlie is the morbidly obese, reclusive English teacher at the center of Darren Aronofsky’s film "The Whale," whose attempts to reconnect with his estranged daughter drive the story’s emotional core.
  • A. Charlie chosen
    Charlie is the reclusive, morbidly obese English professor at the center of Darren Aronofsky’s film "The Whale," whose struggle with grief, guilt, and self-destruction drives the story’s emotional core.
  • B. Charlie
    Charlie is Dory’s loving but forgetful father in the animated film "Finding Dory," known for his patience, optimism, and inventive ways of helping her cope with memory loss.
  • C. Charlie
    Charlie is the central protagonist in the romantic film "Love, Wedding, Marriage," around whom the story’s relationship and marital themes revolve.
  • D. Charlie
    Charlie is the central protagonist of the film "The Business," around whom the story’s criminal and dramatic events revolve.
  • E. Charlie
    Charlie is a central character in the indie film "Happythankyoumoreplease," portrayed as a young New Yorker navigating relationships, personal growth, and the search for meaning.
  • F. None of above.

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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e673a5ce4081908dff86ed4c613fd6 completed April 20, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a085a1759d081909909d30925d03d72 completed May 16, 2026, 11:50 a.m.
NEDg Description generation batch_6a085ad8bfd08190ac31b66cdc0bc6aa completed May 16, 2026, 11:54 a.m.
NED2 Entity disambiguation (via description) batch_6a085b756f44819090892ab35a98fcc8 completed May 16, 2026, 11:56 a.m.
Created at: April 11, 2026, 11:41 p.m.