Triple

T19715528
Position Surface form Disambiguated ID Type / Status
Subject Cynthia Jane Williams E473466 entity
Predicate alsoKnownAs P39 FINISHED
Object Cindy Williams NE NERFINISHED

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: [Cynthia Jane Williams, alsoKnownAs, Cindy Williams]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cindy Williams
Context triple: [Cynthia Jane Williams, alsoKnownAs, 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. Cindy Williams
    Cindy Williams is a screenwriter known for her work on the influential 1977 car-chase film "Grand Theft Auto."
  • D. 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.
  • E. 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."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6440cb47c81908124dfbd6f781d23 completed April 20, 2026, 3:19 p.m.
Created at: April 10, 2026, 1:46 p.m.