Nouns dominate because the English lexicon contains many concrete nouns, compound nouns, and nominalizations.
We used the version 0.7b, containing over 134,000 English words with phonetic transcriptions. This dictionary includes inflected forms (e.g., ‘runs’, ‘running’) and proper nouns. 10000 random words
This study analyzes a random sample of 10,000 English words to determine fundamental statistical properties, including length distribution, character frequency, syllable count, and part-of-speech diversity. Using a pseudorandom selection from a standardized word list, we find that the average English word length is approximately 9.3 characters, with a strong left-skewed distribution toward shorter words. Vowels (particularly ‘e’) dominate character frequency, while function words (e.g., ‘the’, ‘of’, ‘and’) appear less frequently than expected due to the random sampling method. The results provide a baseline for understanding English lexical structure without corpus-based frequency biases. Nouns dominate because the English lexicon contains many
Zipf’s law states that word frequency is inversely proportional to rank in a corpus. However, our random sample shows no Zipfian distribution; instead, all words appear exactly once. This reinforces that Zipf’s law is a property of language use, not of the lexicon. This study analyzes a random sample of 10,000
In software development, "10,000 random words" is a common benchmark for testing the efficiency of algorithms and UI components.
The dataset aggregates 10,000 unique entries drawn from a standard lexicon. The selection process prioritizes true randomness, ensuring a heterogeneous mix of: