Semantic Fields

H4 asks whether dictionaries show measurable topical coverage profiles when their headword sets are projected onto the Amarakosa's native varga taxonomy. This page is dictionary-first: it uses generated dictionary headword evidence only, not corpus frequency, standards exports, or GitHub activity.

Trust Block

• Evidence: data/lexico/semantic_fields.csv, data/lexico/semantic_field_coverage.csv, data/lexico/semantic_field_report.json, scripts/lexico/m8_semantic_fields.py, and scripts/build-semantic-fields.mjs.
• Limitations: headword coverage only; no corpus frequency, passage attestation, sense coverage, or non-headword mentions.
• Validation: generated by npm run build-semantic-fields; source data by python scripts/lexico/validate_lexico.py; page by npm run build.
• Owner repo: csl-atlas.
• Next use: leave H4 as the continuity placeholder until H6 and the headword/subentry microstructure layer are documented, then review the H4 convention samples.

Dictionary Coverage

Core Dictionary Matrix

The matrix is a headword-coverage view. A low cell can mean the dictionary uses prose, citation, or inflected conventions that do not expose every AMAR synonym as a comparable <k1> headword.

Dictionary Rows

How To Read It

• The fields are AMAR vargas, not a modern semantic ontology.
• Coverage means normalized AMAR synonyms found as dictionary <k1> headwords.
• SKD/VCP-style prose and citation conventions can produce false lows.
• The chart supports H4 as a measurable bias layer, not as a final claim about semantic exhaustiveness.

Generated by npm run build-semantic-fields. See docs/MICROSTRUCTURE_SEMANTIC_FIELDS.md. CC-BY-SA-4.0.