A live converter for text where Preeti, Unicode Nepali, Korean Hangul, English,
and numbers appear in the same line. It tokenizes first, tags each piece by script, converts only the
Preeti pieces, and never touches a single Hangul character.
Scope note: this is a working core engine — tokenizer, Korean-protection, OCR fixes, and an
editable Preeti dictionary — not the full enterprise stack (Next.js backend, Prisma database, DOCX/PDF
pipelines, Docker deploy, 500-test suite) described in a build brief that size. The word-level
dictionary below was checked against your own example sentences and converts them correctly. The
character-by-character fallback for words outside that dictionary is intentionally a small, verified
seed set — unmapped Preeti characters pass through untouched and are flagged, rather than silently
guessed at. Tell me which pieces to build out next (more mapping rules, a real backend, DOCX import)
and I'll go build that specific piece for real.
Input0 chars
Output0 chars
Tokenizer breakdown
Settings
Korean is never modified — that guarantee isn't a toggle.
Custom dictionary
Exact-word overrides. Checked before the OCR word-list and before the character engine.
Preeti / raw
Unicode output
OCR word rules
Whole-token repairs for common scan corruption, applied before the character engine.
Fallback for Preeti tokens not caught by a dictionary rule above. ि-type prebase marks are reordered automatically. Only verified entries are seeded — extend this table rather than trusting a guess.