Triple

T7581179
Position Surface form Disambiguated ID Type / Status
Subject The Winds of War E179488 entity
Predicate castMember P1668 FINISHED
Object Lisa Eilbacher E442286 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: Lisa Eilbacher | Statement: [The Winds of War, castMember, Lisa Eilbacher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisa Eilbacher
Context triple: [The Winds of War, castMember, Lisa Eilbacher]
  • A. Lisa Eilbacher chosen
    Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
  • B. Stefanie Ehrlich
    Stefanie Ehrlich is known as a child of the prominent American biologist and author Paul Ehrlich.
  • C. Lisa Bluder
    Lisa Bluder is a longtime head coach of the University of Iowa women's basketball team, known for leading the Hawkeyes to national prominence behind star players like Caitlin Clark.
  • D. Lisa Gottsegen
    Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
  • E. Lisa Lassek
    Lisa Lassek is an American film and television editor known for her frequent collaborations with Joss Whedon on projects such as major Marvel superhero films and cult TV series.
  • 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_69c69f327db881909a21ae3b156f8ded completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f97717048190b0ca1a74ed8a817e completed March 27, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea7b9d020819091342951d00661f9 completed April 2, 2026, 5:30 p.m.
Created at: March 27, 2026, 3:52 p.m.