Triple

T4441186
Position Surface form Disambiguated ID Type / Status
Subject Eraser E95773 entity
Predicate starring P1507 FINISHED
Object John Slattery E140016 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: John Slattery | Statement: [Eraser, starring, John Slattery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Slattery
Context triple: [Eraser, starring, John Slattery]
  • A. John Slattery chosen
    John Slattery is an American actor and director best known for his role as Roger Sterling on the television series "Mad Men."
  • B. Donald Faison
    Donald Faison is an American actor and comedian best known for his role as Dr. Christopher Turk on the television series "Scrubs."
  • C. Peter Krause
    Peter Krause is an American actor best known for his leading roles in television dramas such as Six Feet Under, Sports Night, and Parenthood.
  • D. Matthew Weiner
    Matthew Weiner is an American television writer, director, and producer best known for creating the critically acclaimed series "Mad Men."
  • E. Adrian Grenier
    Adrian Grenier is an American actor best known for starring as Vincent Chase on the television series "Entourage" and appearing in several popular films.
  • 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_69b3453ea2b48190a26f154b3b8fece5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355ad71588190b1dcad4250472c29 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b61380fca08190bf036a7d82cee0e7 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:32 p.m.