Triple

T2704233
Position Surface form Disambiguated ID Type / Status
Subject Sesame Street E59304 entity
Predicate notableCharacter P1481 FINISHED
Object Cookie Monster
Cookie Monster is a beloved blue, googly-eyed Muppet best known for his voracious appetite for cookies and his appearances on the children's television show Sesame Street.
 E290271 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: Cookie Monster | Statement: [Sesame Street, notableCharacter, Cookie Monster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cookie Monster
Context triple: [Sesame Street, notableCharacter, Cookie Monster]
  • A. Mad Mouse
    Mad Mouse is a compact steel wild mouse–style roller coaster located at the Michigan’s Adventure amusement park in Michigan.
  • B. Wendy
    Wendy is a character portrayed by actress and model Jamie King, known from her work in film and television.
  • C. Bert
    Bert is the given name of Bert Hölldobler, a renowned German behavioral biologist and sociobiologist known for his pioneering research on ants and social insects.
  • D. Bert
    Bert is a film director best known for co-directing the 2019 coming-of-age comedy-drama "Troop Zero."
  • E. Bert
    Bert is a Swedish film or television production best known as an early directorial work by acclaimed filmmaker Tomas Alfredson.
  • 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: Cookie Monster
Triple: [Sesame Street, notableCharacter, Cookie Monster]
Generated description
Cookie Monster is a beloved blue, googly-eyed Muppet best known for his voracious appetite for cookies and his appearances on the children's television show Sesame Street.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cookie Monster
Target entity description: Cookie Monster is a beloved blue, googly-eyed Muppet best known for his voracious appetite for cookies and his appearances on the children's television show Sesame Street.
  • A. Mad Mouse
    Mad Mouse is a compact steel wild mouse–style roller coaster located at the Michigan’s Adventure amusement park in Michigan.
  • B. Wendy
    Wendy is a character portrayed by actress and model Jamie King, known from her work in film and television.
  • C. Bert
    Bert is a film director best known for co-directing the 2019 coming-of-age comedy-drama "Troop Zero."
  • D. Bert
    Bert is a Swedish film or television production best known as an early directorial work by acclaimed filmmaker Tomas Alfredson.
  • E. Bert
    Bert is the given name of Bert Hölldobler, a renowned German behavioral biologist and sociobiologist known for his pioneering research on ants and social insects.
  • 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_69ab4ac66bc88190b9e4afa5fc843f72 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda518c58819096c8b67c0f754655 completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf79c8648190a9041dd2903a1429 completed March 10, 2026, 5:43 a.m.
NEDg Description generation batch_69afb002b86881909401e1bec24b76bf completed March 10, 2026, 5:45 a.m.
NED2 Entity disambiguation (via description) batch_69afb0e906f88190b182cbfe81122eed completed March 10, 2026, 5:49 a.m.
Created at: March 6, 2026, 9:55 p.m.