Triple

T13004912
Position Surface form Disambiguated ID Type / Status
Subject Breckin Meyer E322260 entity
Predicate familyName P18 FINISHED
Object Meyer E345534 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: Meyer | Statement: [Breckin Meyer, familyName, Meyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meyer
Context triple: [Breckin Meyer, familyName, Meyer]
  • A. Meyer chosen
    Meyer is a common German-origin surname borne by numerous notable individuals across fields such as literature, entertainment, sports, and academia.
  • B. Meyer
    Meyer is a given name most famously associated with Meyer Lansky, a major organized crime figure in the United States during the 20th century.
  • C. Meier
    Meier is a common German surname borne by numerous individuals across various professions and regions.
  • D. Mayer
    Mayer is a common German-origin surname borne by numerous notable individuals across fields such as music, science, and politics.
  • E. Meyer-Hetling
    Meyer-Hetling is a German surname most notably associated with Konrad Meyer-Hetling, an agronomist and SS officer involved in Nazi settlement planning.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9a2a448190968833354280e474 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c107f990819093042560b1bc4473 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:48 p.m.