Triple

T20558458
Position Surface form Disambiguated ID Type / Status
Subject Jessica Szohr E504781 entity
Predicate characterRole P268 FINISHED
Object Vanessa Abrams 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: Vanessa Abrams | Statement: [Jessica Szohr, characterRole, Vanessa Abrams]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vanessa Abrams
Context triple: [Jessica Szohr, characterRole, Vanessa Abrams]
  • A. Vanessa Abrams chosen
    Vanessa Abrams is a socially conscious, bohemian filmmaker and Dan Humphrey’s longtime friend and love interest on the television series "Gossip Girl."
  • B. Vanessa Brown
    Vanessa Brown was an Austrian-born American actress known for her work in mid-20th-century Hollywood films, radio, and stage productions.
  • C. Vanessa Howard
    Vanessa Howard was a British actress known for her roles in 1960s and 1970s horror and exploitation films, including "The Blood Beast Terror" and "Mumsy, Nanny, Sonny & Girly."
  • D. Vanessa Roth
    Vanessa Roth is an Academy Award-winning American documentary filmmaker known for her socially conscious films and work in education and social justice.
  • E. Vanessa Woods
    Vanessa Woods is an Australian science writer and researcher known for her work on primate cognition and her popular science books about dogs, bonobos, and human evolution.
  • 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_69e0b4b6587c8190aee63dc7cff244ea completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a5df84088190848c7eb35564d8f9 completed April 20, 2026, 10:17 p.m.
Created at: April 16, 2026, 11:38 a.m.