Triple

T639422
Position Surface form Disambiguated ID Type / Status
Subject Jane Wyman E16699 entity
Predicate name P16 FINISHED
Object Jane Wyman E16699 NE FINISHED

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: [Jane Wyman, name, Jane Wyman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jane Wyman
Context triple: [Jane Wyman, name, 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. 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.
  • C. Hailee Steinfeld
    Hailee Steinfeld is an American actress and pop singer known for her Oscar-nominated role in "True Grit" and hit songs like "Love Myself" and "Starving."
  • D. Anya Taylor-Joy
    Anya Taylor-Joy is an award-winning actress known for her breakout role in "The Queen's Gambit" and performances in films such as "The Witch," "Split," and "Last Night in Soho."
  • E. Mackenzie Foy
    Mackenzie Foy is an American actress and model best known for her role as Renesmee Cullen in the Twilight film series and for starring in films such as Interstellar and The Nutcracker and the Four Realms.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a4936be1c88190af56540324b57da7 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49f00260081909d1a679182e23d10 completed March 1, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc93fd28819088ece7790ff19270 completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:35 p.m.