Triple

T15625173
Position Surface form Disambiguated ID Type / Status
Subject Partly Cloudy E375659 entity
Predicate hasCharacter P2308 FINISHED
Object Gus
Gus is the lonely but gentle gray cloud in Pixar’s short film "Partly Cloudy," known for creating dangerous baby animals for his stork partner to deliver.
 E1167766 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: Gus | Statement: [Partly Cloudy, hasCharacter, Gus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gus
Context triple: [Partly Cloudy, hasCharacter, Gus]
  • A. Gus
    Gus is the given name of American filmmaker Gus Van Sant, known for directing independent and mainstream films such as "Good Will Hunting" and "Milk."
  • B. Gus
    Gus is the lovable, chubby mouse in Disney's 1950 animated film "Cinderella," known for his comic relief and loyal friendship to Cinderella.
  • C. Gus
    Gus is the nickname of Virgil "Gus" Grissom, one of NASA's original Mercury Seven astronauts and a pioneering American spacefarer.
  • D. Gus
    Gus is a 1976 Disney sports comedy film about a football team that gains an unlikely advantage from a field-goal-kicking mule.
  • E. Gus
    Gus is one of the two hitmen at the center of Harold Pinter’s play "The Dumb Waiter," known for his anxious, questioning nature and tense exchanges in the basement setting.
  • 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: Gus
Triple: [Partly Cloudy, hasCharacter, Gus]
Generated description
Gus is the lonely but gentle gray cloud in Pixar’s short film "Partly Cloudy," known for creating dangerous baby animals for his stork partner to deliver.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gus
Target entity description: Gus is the lonely but gentle gray cloud in Pixar’s short film "Partly Cloudy," known for creating dangerous baby animals for his stork partner to deliver.
  • A. Gus
    Gus is the lovable, chubby mouse in Disney's 1950 animated film "Cinderella," known for his comic relief and loyal friendship to Cinderella.
  • B. Gus
    Gus is the affectionate nickname of Burton "Gus" Guster, the loyal and often cautious best friend and business partner in the TV series "Psych."
  • C. Gus
    Gus is a main character in the Disney XD series "Mighty Med," known as a comedic, somewhat dim-witted teen who helps run a secret superhero hospital with his best friend.
  • D. Gus
    Gus is a character from T. S. Eliot's "Old Possum's Book of Practical Cats," depicted as an elderly, once-famous theater cat reflecting nostalgically on his past glory.
  • E. Gus
    Gus is a 1976 Disney sports comedy film about a football team that gains an unlikely advantage from a field-goal-kicking mule.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f3f65dc8190ac94db1d4d53d77f completed May 9, 2026, 4:22 p.m.
NEDg Description generation batch_69ff60188df48190a1cc891757a795d0 completed May 9, 2026, 4:26 p.m.
NED2 Entity disambiguation (via description) batch_69ff60938ef081908cd88cf8242bc785 completed May 9, 2026, 4:28 p.m.
Created at: April 10, 2026, 4:14 a.m.