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How to measure morphological complexity is itself an issue of some complexity. (Nichols, 1992) This article develops an information‐theoretic and functionally motivated method of measuring “linguistic complexity”; from corpora that can in theory be applied to any definable substructure. This method is further extended into a way of objectively and numerically measuring the morphological complexity of a given language sample, avoiding the typical difficulties of focusing on only a few unrepresentative types of constructions. By selectively altering the morphological information present in a sample, the complexity can be measured as the change in overall informativeness of a text. This claim has been tested in a small‐scale cross‐linguistic experiment; the results agree well with both intuitions and existing measurements.
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Stored only when both papers are in the corpus — 111 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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