For many models oflexical ambiguity resolution, relative frequency of the different meanings of homographs (words with more than one meaning) is crucial. Although several homograph as-sociation norms have been published in the past, none has involved a large number of subjects responding to a large number of homographs, and most homograph norming studies are now at least a decade old. In Experiment 1, associations to 566 homographs were collected from an aver-age of 192 subjects per homograph. Frequency of occurrence for the three most common mean-ings is reported, along with the corresponding associates, and a measure of the overall ambiguity of each homograph. Homographs whose meanings differed in part of speech were more ambigu-ous overall than homographs whose different meanings belonged to a single grammatical class. Homographs whose pronunciation depended on meaning (heterophones) were no more ambigu-ous than nonheterophones, and word frequency was unrelated to overall ambiguity. Estimates of homograph balance across different norming studies were compared, and homographs with two meanings of approximately equal relative meaning frequency (balanced homographs) and homographs with one clearly dominant meaning (polarized homographs) were identified. In Ex-periment 2, reliability of meaning categorizations was measured for a subset of the homographs in the first experiment. Meaning categorizations were shown to be highly reliable across raters. Homographs are words that have more than one mean-ing but share the same orthography. They most often also share phonology (e.g., a dog's bark vs. a tree's bark; a fireplace poker vs. a poker game), but a few English homographs have distinct phonologies for their different meanings. For these heterophonic homographs, pronun-ciation depends on meaning; examples are "bass" (fish vs. guitar) and "wind" (gale vs. to coil). Contrary to in-tuition, homographs are not an obscure class of linguistic items. Rather, homographs could be considered impor-tant topics of study solely because of their abundance in English. Britton (1978) found that 44 {\%} of a random sam-ple of English words had more than one meaning, and that 85 {\%} of a sample of high-frequency English words