Triple

T10207265
Position Surface form Disambiguated ID Type / Status
Subject Jell-O E242231 entity
Predicate foundedBy P104 FINISHED
Object Pearle Wait
Pearle Wait was an American inventor and entrepreneur best known for creating the gelatin dessert brand Jell-O in the late 19th century.
 E849447 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: Pearle Wait | Statement: [Jell-O, foundedBy, Pearle Wait]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pearle Wait
Context triple: [Jell-O, foundedBy, Pearle Wait]
  • A. Pearl Aday
    Pearl Aday is an American rock singer and songwriter, best known as the daughter of rock musician Meat Loaf and for her work as a backing vocalist and solo artist.
  • B. Pearl Gibbs
    Pearl Gibbs was a prominent Aboriginal Australian activist and organizer who played a key role in early 20th-century campaigns for Indigenous rights and justice.
  • C. Beverly Kane
    Beverly Kane is known as the wife of Bob Kane, the American comic book artist and co-creator of Batman.
  • D. Lurene Tuttle
    Lurene Tuttle was an American character actress known for her prolific work in radio, film, and television from the 1930s through the 1970s.
  • E. Mary Wills
    Mary Wills was an American costume designer known for her work on major mid-20th-century Hollywood films and for winning an Academy Award for Best Costume Design.
  • 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: Pearle Wait
Triple: [Jell-O, foundedBy, Pearle Wait]
Generated description
Pearle Wait was an American inventor and entrepreneur best known for creating the gelatin dessert brand Jell-O in the late 19th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pearle Wait
Target entity description: Pearle Wait was an American inventor and entrepreneur best known for creating the gelatin dessert brand Jell-O in the late 19th century.
  • A. Pearl Aday
    Pearl Aday is an American rock singer and songwriter, best known as the daughter of rock musician Meat Loaf and for her work as a backing vocalist and solo artist.
  • B. Pearl Gibbs
    Pearl Gibbs was a prominent Aboriginal Australian activist and organizer who played a key role in early 20th-century campaigns for Indigenous rights and justice.
  • C. Beverly Kane
    Beverly Kane is known as the wife of Bob Kane, the American comic book artist and co-creator of Batman.
  • D. Lurene Tuttle
    Lurene Tuttle was an American character actress known for her prolific work in radio, film, and television from the 1930s through the 1970s.
  • E. Mary Wills
    Mary Wills was an American costume designer known for her work on major mid-20th-century Hollywood films and for winning an Academy Award for Best Costume Design.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d395f8e2b881909c51f8210f09cd4f completed April 6, 2026, 11:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d652c13d748190908d1869c60e84c3 completed April 8, 2026, 1:06 p.m.
NEDg Description generation batch_69d653c9f3e48190a51f6c6285d55e1d completed April 8, 2026, 1:10 p.m.
NED2 Entity disambiguation (via description) batch_69d65433b62081908895b50139b3de3f completed April 8, 2026, 1:12 p.m.
Created at: April 6, 2026, 10:55 a.m.