Triple

T1749554
Position Surface form Disambiguated ID Type / Status
Subject Lie to Me E38406 entity
Predicate hasProtagonist P8706 FINISHED
Object Cal Lightman E197298 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: Cal Lightman | Statement: [Lie to Me, hasProtagonist, Cal Lightman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cal Lightman
Context triple: [Lie to Me, hasProtagonist, Cal Lightman]
  • A. Dr. Cal Lightman chosen
    Dr. Cal Lightman is a brilliant but abrasive deception expert who leads a team that uses facial expressions and body language to uncover the truth in the TV series "Lie to Me."
  • B. Michael Graydon
    Michael Graydon is a retired senior Royal Air Force officer who served as a leading commander of British fighter aviation during the late 20th century.
  • C. John Dawson
    John Dawson was a pioneering American plasma physicist renowned for his foundational contributions to plasma theory and fusion research.
  • D. Dorian Sagan
    Dorian Sagan is an American science writer and essayist known for his works on evolution, complexity, and the philosophy of science, often co-authored with his mother, biologist Lynn Margulis.
  • E. Michael V. Drake
    Michael V. Drake is an American academic leader and physician who has served as president of both The Ohio State University and the University of California system.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64108a208190ae7190065818e42c completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada989b368819098b788d099f2f8e4 completed March 8, 2026, 4:53 p.m.
Created at: March 4, 2026, 7:31 p.m.