Triple

T15312169
Position Surface form Disambiguated ID Type / Status
Subject A Simple Favor E366063 entity
Predicate screenwriter P2831 FINISHED
Object Jessica Sharzer 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: Jessica Sharzer | Statement: [A Simple Favor, screenwriter, Jessica Sharzer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jessica Sharzer
Context triple: [A Simple Favor, screenwriter, Jessica Sharzer]
  • A. Jessica Sharzer chosen
    Jessica Sharzer is an American screenwriter, director, and producer known for her work in film and television, including adaptations and genre projects.
  • B. Lisa Gottsegen
    Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
  • C. Jessica Pressler
    Jessica Pressler is an American journalist and writer best known for her New York magazine feature on a group of strip-club scammers that inspired the film "Hustlers."
  • D. Jessica Szohr
    Jessica Szohr is an American actress best known for her role as Vanessa Abrams on the television series "Gossip Girl" and later as a main cast member on the sci-fi comedy-drama "The Orville."
  • E. Jessica Tuchinsky
    Jessica Tuchinsky is a television and film producer known for her executive production work on the miniseries adaptation of John Green's novel "Looking for Alaska."
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03cd2d5a88190aead748920f93d47 completed April 16, 2026, 1:35 a.m.
Created at: April 10, 2026, 3:16 a.m.