Triple

T23290043
Position Surface form Disambiguated ID Type / Status
Subject Waterfront E589999 entity
Predicate musicBy P1952 FINISHED
Object William Lava 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: William Lava | Statement: [Waterfront, musicBy, William Lava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Lava
Context triple: [Waterfront, musicBy, William Lava]
  • A. William Lava chosen
    William Lava was an American composer best known for scoring numerous Warner Bros. cartoons, including many Looney Tunes and Merrie Melodies shorts.
  • B. John Latta
    John Latta was an American politician who became the inaugural lieutenant governor of Pennsylvania in the late 19th century.
  • C. Robert Lavette
    Robert Lavette is a former American football running back best known for his standout college career at Georgia Tech and his time in the NFL with the Dallas Cowboys and Philadelphia Eagles.
  • D. John Lowin
    John Lowin was a prominent early 17th-century English actor associated with Shakespeare’s company, known for performing major roles in Jacobean and Caroline drama.
  • E. William LeVanway
    William LeVanway was a film editor active during early Hollywood cinema, known for his work on the musical revue film "Hollywood Revue of 1929."
  • 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_69e25d1af9d88190a0b9b5e8fa608618 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1964a4c548190bda1e85b8d316e8a completed April 29, 2026, 5:25 a.m.
Created at: April 17, 2026, 5:01 p.m.