Triple

T21291415
Position Surface form Disambiguated ID Type / Status
Subject Charles D. King E524798 entity
Predicate employer P7 FINISHED
Object MACRO 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: MACRO | Statement: [Charles D. King, employer, MACRO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MACRO
Context triple: [Charles D. King, employer, MACRO]
  • A. MACRO chosen
    MACRO is an American media and entertainment company focused on producing and financing film and television projects that center Black people and other people of color.
  • B. Macro
    Macro was a powerful Roman official who served as praetorian prefect, effectively controlling the imperial guard and wielding significant influence in the politics of the early Roman Empire.
  • C. the macroprosopus
    The Macroprosopus is a kabbalistic term for the transcendent, hidden aspect of the divine associated with the highest sefirah and the primordial divine countenance.
  • D. MACRO-11
    MACRO-11 is the assembly language for DEC's PDP-11 minicomputers, widely used for low-level systems and application programming on RSX-11 and related operating systems.
  • E. MICRO
    MICRO is a leading annual international conference focused on microarchitecture and advanced computer architecture research.
  • 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736da28648190ae3f63c6ba1f6d6f completed April 21, 2026, 8:35 a.m.
Created at: April 16, 2026, 4:04 p.m.