Triple

T17973561
Position Surface form Disambiguated ID Type / Status
Subject Two-Face E449405 entity
Predicate portrayedBy P1507 FINISHED
Object Aaron Eckhart 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: Aaron Eckhart | Statement: [Two-Face, portrayedBy, Aaron Eckhart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aaron Eckhart
Context triple: [Two-Face, portrayedBy, Aaron Eckhart]
  • A. Aaron Eckhart chosen
    Aaron Eckhart is an American actor best known for his roles in films such as "The Dark Knight," "Thank You for Smoking," and "Erin Brockovich."
  • B. Giovanni Ribisi
    Giovanni Ribisi is an American actor known for his character roles in films like "Saving Private Ryan," "Avatar," and the TV series "Friends."
  • C. Bill Hartnett
    Bill Hartnett is a person notable enough to be recognized as a bearer of the surname Hartnett, though specific widely known achievements or roles are not clearly documented.
  • D. Michael Bell
    Michael Bell is an American voice actor known for his extensive work in animated television series, films, and video games since the 1970s.
  • E. Jay Levey
    Jay Levey is an American film and music video director best known for directing "Weird Al" Yankovic’s 1989 cult comedy film *UHF* and many of the musician’s iconic videos.
  • 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b1fca04481908f0dd875953fd82f completed April 19, 2026, 10:44 a.m.
Created at: April 10, 2026, 10:22 a.m.