Triple

T9810450
Position Surface form Disambiguated ID Type / Status
Subject Spotlight E238253 entity
Predicate stars P1956 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: [Spotlight, stars, John Slattery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Slattery
Context triple: [Spotlight, stars, 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_69ca84defac48190abc1148804f184c1 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb220310c8190a16ca0b746f0ef7a completed April 2, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc5b4dd8819088c86946b4eb8a39 completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:30 p.m.