Triple

T19547185
Position Surface form Disambiguated ID Type / Status
Subject So Big (1953 film) E489103 entity
Predicate starring P1507 FINISHED
Object Jane Wyman 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: Jane Wyman | Statement: [So Big (1953 film), starring, Jane Wyman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jane Wyman
Context triple: [So Big (1953 film), starring, Jane Wyman]
  • A. Jane Wyman chosen
    Jane Wyman was an American actress and Academy Award winner best known for her film and television work in the mid-20th century.
  • B. Taylor Russell
    Taylor Russell is a Canadian actress best known for her breakout role in the Netflix sci-fi series "Lost in Space" and acclaimed performances in films such as "Waves" and "Bones and All."
  • C. Haley Bennett
    Haley Bennett is an American actress and singer known for her versatile performances in films such as "The Girl on the Train," "The Magnificent Seven," and "Swallow."
  • D. Dakota Fanning
    Dakota Fanning is an American actress who rose to fame as a child star in films like "I Am Sam" and has since built a diverse career in both mainstream and independent cinema.
  • E. Elle Fanning
    Elle Fanning is an American actress known for her versatile performances in films such as "Super 8," "Maleficent," and "The Neon Demon," as well as the TV series "The Great."
  • 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63d2d8a6081908e9bb3a6f5d85896 completed April 20, 2026, 2:50 p.m.
Created at: April 10, 2026, 1:41 p.m.