Triple

T16100439
Position Surface form Disambiguated ID Type / Status
Subject Laurie Henderson E390602 entity
Predicate portrayedBy P1507 FINISHED
Object Cindy Williams E103739 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: Cindy Williams | Statement: [Laurie Henderson, portrayedBy, Cindy Williams]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cindy Williams
Context triple: [Laurie Henderson, portrayedBy, Cindy Williams]
  • A. Cindy Williams chosen
    Cindy Williams was an American actress best known for her role as Shirley Feeney on the hit television sitcom "Laverne & Shirley."
  • B. Cindy Williams
    Cindy Williams is a fictional character from the British soap opera "EastEnders," known for her tumultuous relationships and connections to the Beale family.
  • C. JoBeth Williams
    JoBeth Williams is an American actress known for her roles in films such as "Poltergeist," "The Big Chill," and numerous television movies and series.
  • D. June Lockhart
    June Lockhart is an American actress best known for her roles in classic television series such as "Lassie" and the original "Lost in Space."
  • E. Nancy Kyes
    Nancy Kyes is an American actress best known for her roles in John Carpenter films, including the original Halloween and Assault on Precinct 13.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6756948190a7f5ecb375e59701 completed April 17, 2026, 9:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00606a3d5c8190a145ca35ce458f7e completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 5 a.m.