Triple
T13203589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SOS |
E314300
|
entity |
| Predicate | associatedWith |
P37
|
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: [SOS, associatedWith, Morse code]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morse code Context triple: [SOS, associatedWith, 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c9961a48190a1157df47f59b7af |
completed | April 10, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a3017bc8190b5481bf02684e861 |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:17 p.m.