Triple

T3112318
Position Surface form Disambiguated ID Type / Status
Subject The Kominsky Method E64978 entity
Predicate starring P1507 FINISHED
Object Sarah Baker E327548 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: Sarah Baker | Statement: [The Kominsky Method, starring, Sarah Baker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarah Baker
Context triple: [The Kominsky Method, starring, Sarah Baker]
  • A. Sarah Baker chosen
    Sarah Baker is an American actress and comedian known for her work in television and film, including a prominent role on the Netflix series "The Kominsky Method."
  • B. Sophie Baker
    Sophie Baker is known as the wife of acclaimed English actor Ian Holm.
  • C. Sarah Barnard
    Sarah Barnard was the wife of renowned English scientist Michael Faraday, providing personal support throughout his career in 19th-century London.
  • D. Sarah Eaves
    Sarah Eaves was the partner and later wife of the renowned English printer and typographer John Baskerville, closely involved in his household and business affairs.
  • E. Rosalie Booth
    Rosalie Booth was a 19th-century American woman best known as a member of the prominent Booth theatrical family, which included several famous stage actors.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada43b0b3c8190a828c9cfcf730ed9 completed March 8, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f5cfc7c8190b867794c0e9a271e completed March 12, 2026, 12:57 a.m.
Created at: March 8, 2026, 3:04 p.m.