Triple

T13032009
Position Surface form Disambiguated ID Type / Status
Subject Sayonara E326463 entity
Predicate starring P1507 FINISHED
Object Martha Scott E283962 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: Martha Scott | Statement: [Sayonara, starring, Martha Scott]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martha Scott
Context triple: [Sayonara, starring, Martha Scott]
  • A. Martha Scott chosen
    Martha Scott was an American actress known for her work in film, television, and theater, including prominent roles in classic Hollywood epics.
  • B. Martha Pattridge
    Martha Pattridge is known as the wife of longtime Manhattan District Attorney Robert M. Morgenthau.
  • C. Martha Hunt
    Martha Hunt is an American fashion model best known for her work with Victoria’s Secret, including serving as a Victoria’s Secret Angel.
  • D. Catherine Amy Dawson Scott
    Catherine Amy Dawson Scott was a British novelist and playwright best known for founding PEN International, the worldwide association of writers.
  • E. Martha McMillan Roberts
    Martha McMillan Roberts was a Farm Security Administration photographer known for documenting American life during the Great Depression era.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97efe72348190b52fb4068f5fb829 completed April 10, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff01ce8f988190b503af0cd5f2a97e completed May 9, 2026, 9:43 a.m.
Created at: April 9, 2026, 8:54 p.m.