Triple

T20029033
Position Surface form Disambiguated ID Type / Status
Subject Ever After E495070 entity
Predicate writer P1360 FINISHED
Object Susannah Grant 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: Susannah Grant | Statement: [Ever After, writer, Susannah Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susannah Grant
Context triple: [Ever After, writer, Susannah Grant]
  • A. Susannah Grant chosen
    Susannah Grant is an American screenwriter, director, and producer best known for writing the film "Erin Brockovich" and creating several television series.
  • B. Susannah Hill
    Susannah Hill was an English noblewoman best known as the wife of Edward Montagu, 2nd Earl of Manchester, a prominent 17th-century politician and military commander.
  • C. Susannah York
    Susannah York was an acclaimed English actress known for her versatile performances in film, television, and theatre during the 1960s and 1970s.
  • D. Susannah Martin
    Susannah Martin was a Massachusetts woman executed for alleged witchcraft in 1692, remembered as one of the victims of the Salem witch trials.
  • E. Susannah French
    Susannah French was a colonial American woman best known as the mother of Sarah Van Brugh Livingston, who became a prominent figure in early United States political and social circles.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662908df081909a6c8ccf0dd90fff completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:36 p.m.