Triple

T9009167
Position Surface form Disambiguated ID Type / Status
Subject Lie to Me E215423 entity
Predicate creator P184 FINISHED
Object Samuel Baum E215423 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: Samuel Baum | Statement: [Lie to Me, creator, Samuel Baum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samuel Baum
Context triple: [Lie to Me, creator, Samuel Baum]
  • A. Samuel Baum chosen
    Samuel Baum is a television writer and producer best known for creating the crime drama series "Lie to Me."
  • B. Samuel Blum
    Samuel Blum is a relatively obscure individual whose specific notability is not clearly established from the given information.
  • C. Samuel Diescher
    Samuel Diescher was a prominent 19th-century civil and mechanical engineer known for designing several American inclines and industrial structures, particularly in Pittsburgh.
  • D. Samuel Weiss
    Samuel Weiss is a relatively obscure individual whose specific public significance is not clearly established from the available information.
  • E. Samuel Rubin
    Samuel Rubin was a philanthropist and businessman best known for founding the Samuel Rubin Foundation, which supported social justice, peace, and human rights initiatives.
  • 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69bed8588190afc9cbca12b75a3b completed April 1, 2026, 12:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfeb671e488190920fb1780e4ad48d completed April 3, 2026, 4:31 p.m.
Created at: March 30, 2026, 7:06 p.m.