Triple

T20645602
Position Surface form Disambiguated ID Type / Status
Subject The Station Agent E507346 entity
Predicate producer P490 FINISHED
Object Mary Jane Skalski 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: Mary Jane Skalski | Statement: [The Station Agent, producer, Mary Jane Skalski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Jane Skalski
Context triple: [The Station Agent, producer, Mary Jane Skalski]
  • A. Mary Jane Skalski chosen
    Mary Jane Skalski is an American independent film producer known for her work on acclaimed character-driven dramas such as "The Visitor."
  • B. Mary Ann Winkowski
    Mary Ann Winkowski is a self-described real-life ghost whisperer and paranormal consultant whose experiences with spirits inspired the television series "Ghost Whisperer."
  • C. Mary Jane Paul
    Mary Jane Paul is the ambitious, career-driven television news anchor and complex protagonist at the center of the drama series "Being Mary Jane."
  • D. Janine Jackowski
    Janine Jackowski is a German film producer known for her work on acclaimed independent and art-house films.
  • E. Margaret Domka
    Margaret Domka is an American soccer referee known for officiating at the highest levels of the women’s game, including major domestic and international competitions.
  • 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_69e0b4be702c8190a3d2410a881d310a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6af1dd79481909de985d03ab861c2 completed April 20, 2026, 10:56 p.m.
Created at: April 16, 2026, 11:43 a.m.