Triple

T19244995
Position Surface form Disambiguated ID Type / Status
Subject Curly Top E481226 entity
Predicate character P662 FINISHED
Object Edward Morgan NE NERFINISHED

How this triple was built (2 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: Edward Morgan | Statement: [Curly Top, character, Edward Morgan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edward Morgan
Context triple: [Curly Top, character, Edward Morgan]
  • A. Edward Morgan chosen
    Edward Morgan is a fictional character from the 1935 musical film "Curly Top," which starred Shirley Temple.
  • B. Arthur Lyttelton
    Arthur Lyttelton was a 19th-century English Anglican clergyman and academic who became the first Master of Selwyn College, Cambridge.
  • C. John Julius
    John Julius Angerstein was an 18th–19th century London-based merchant, philanthropist, and art collector whose collection formed the nucleus of the National Gallery.
  • D. Edwin Denison Morgan
    Edwin Denison Morgan was a 19th-century American politician, businessman, and Civil War-era governor of New York who also served as a U.S. senator and influential Republican Party leader.
  • E. Spencer Gore
    Spencer Gore was a pioneering early 20th-century British painter associated with the Camden Town Group, known for his post-Impressionist landscapes and urban scenes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8cd9d1081908a181d02b88b59b8 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5faf47820819081e8b6af852bb1dd completed April 20, 2026, 10:07 a.m.
Created at: April 10, 2026, 1:27 p.m.