Triple

T18383861
Position Surface form Disambiguated ID Type / Status
Subject Beth Ostrosky Stern E446527 entity
Predicate birthName P65 FINISHED
Object Beth Ostrosky 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: Beth Ostrosky | Statement: [Beth Ostrosky Stern, birthName, Beth Ostrosky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beth Ostrosky
Context triple: [Beth Ostrosky Stern, birthName, Beth Ostrosky]
  • A. Beth Ostrosky Stern chosen
    Beth Ostrosky Stern is an American model, actress, author, and animal-rights advocate known for her work in pet rescue and her marriage to radio personality Howard Stern.
  • B. Liz Gorinsky
    Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
  • C. Rachel Leibowitz
    Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
  • D. Julie Roginsky
    Julie Roginsky is a Democratic political consultant and television commentator who gained national attention for accusing Fox News chairman Roger Ailes of sexual harassment.
  • E. Marla Sokoloff
    Marla Sokoloff is an American actress known for her roles in films and television series such as "Dude, Where's My Car?" and "The Practice."
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5179da1048190944398e229e7a4c1 completed April 19, 2026, 5:57 p.m.
Created at: April 10, 2026, 10:45 a.m.