Triple

T18094091
Position Surface form Disambiguated ID Type / Status
Subject Bad Luck Streak in Dancing School E433039 entity
Predicate hasPart P35 FINISHED
Object Bill Lee 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: Bill Lee | Statement: [Bad Luck Streak in Dancing School, hasPart, Bill Lee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bill Lee
Context triple: [Bad Luck Streak in Dancing School, hasPart, Bill Lee]
  • A. Bill Lee chosen
    Bill Lee is an American jazz bassist and composer best known for his film scores, particularly for several of his son Spike Lee’s early movies.
  • B. Bill Lee
    Bill Lee was an American playback singer best known for providing the singing voices for numerous characters in classic Disney films.
  • C. Bill Lee
    Bill Lee is an American businessman and Republican politician serving as the governor of Tennessee.
  • D. Leroy Kirkland
    Leroy Kirkland was an American guitarist, arranger, and songwriter known for his prolific work in R&B and early rock and roll recordings during the mid-20th century.
  • E. Curtis Lee
    Curtis Lee was an American pop singer best known for his early 1960s hits like "Pretty Little Angel Eyes."
  • 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_69d8b907d05c819083cc3bd6021089e6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dd1a75048190924ebc01da83851b completed April 19, 2026, 1:48 p.m.
Created at: April 10, 2026, 10:27 a.m.