Triple

T13929141
Position Surface form Disambiguated ID Type / Status
Subject Samuel Morse E334941 entity
Predicate coDeveloperOf P6901 FINISHED
Object Morse code E320218 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: Morse code | Statement: [Samuel Morse, coDeveloperOf, Morse code]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morse code
Context triple: [Samuel Morse, coDeveloperOf, Morse code]
  • A. Morse code chosen
    Morse code is a system of encoding text characters as sequences of short and long signals (dots and dashes) used historically for long-distance telegraph and radio communication.
  • B. Morse
    Morse is the middle name of Mary Baker Eddy, the founder of Christian Science.
  • C. Morse
    Morse is a surname most famously associated with Samuel Morse, the American inventor and co-developer of the Morse code communication system.
  • D. Morse Signal Devices
    Morse Signal Devices was a company associated with A. Reynolds Morse, likely involved in the development or manufacture of signaling or communication equipment.
  • E. Baconian method
    The Baconian method is a systematic approach to scientific inquiry that emphasizes empirical observation, experimentation, and inductive reasoning to derive general principles from particular facts.
  • 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2aa900a0819095eeb1bc46b0336e completed April 14, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce8262288190a7e6dd647b1917c1 completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 10:16 p.m.