Triple

T21830707
Position Surface form Disambiguated ID Type / Status
Subject Margaret Sanger E538985 entity
Predicate hasChild P369 FINISHED
Object Grant Sanger 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: Grant Sanger | Statement: [Margaret Sanger, hasChild, Grant Sanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grant Sanger
Context triple: [Margaret Sanger, hasChild, Grant Sanger]
  • A. Grant Sanger chosen
    Grant Sanger was one of the children of birth control activist and Planned Parenthood founder Margaret Sanger.
  • B. Mark Sanger
    Mark Sanger is a British film editor best known for his Academy Award–winning work on the science fiction thriller "Gravity."
  • C. Mark Sanger
    Mark Sanger is a fictional character from the 1970s American television series "Ironside," known as the young assistant and bodyguard to wheelchair-bound detective Robert T. Ironside.
  • D. James Sanger
    James Sanger is a British record producer and songwriter known for his work with a wide range of rock and alternative artists.
  • E. Jonathan Sanger
    Jonathan Sanger is an American film producer and director best known for his work on acclaimed films such as "The Elephant Man."
  • 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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0913554508190b81347f01d3903e8 completed April 28, 2026, 10:51 a.m.
Created at: April 16, 2026, 6:54 p.m.