Triple

T14079822
Position Surface form Disambiguated ID Type / Status
Subject Peter Shaw E338836 entity
Predicate stepChild P11545 FINISHED
Object David Shaw E1067265 NE FINISHED

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: David Shaw | Statement: [Peter Shaw, stepChild, David Shaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Shaw
Context triple: [Peter Shaw, stepChild, David Shaw]
  • A. David Shaw
    David Shaw is an American football coach best known for his successful tenure as head coach of Stanford University's football program in the 2010s.
  • B. David Shaw
    David Shaw was an American screenwriter known for his work in mid-20th-century film and television.
  • C. David Shaw chosen
    David Shaw is the son of American singer and actress Pat Suzuki.
  • D. John Bloom
    John Bloom is a film editor best known for his Academy Award-winning work on movies such as "Gandhi" and his editing contributions to notable films including "Charlie Wilson's War."
  • E. David Harrington
    David Harrington is a central character in Tyler Perry's drama series "The Haves and the Have Nots," known as a wealthy, politically connected attorney whose personal and professional conflicts drive much of the show's intrigue.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5c5e027881908f610f5bab7598d4 completed April 14, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb672c08081908e1ff9030745776a completed May 7, 2026, 3:57 p.m.
Created at: April 9, 2026, 10:21 p.m.