eDom: Norming software and relative meaning frequencies for 544 English homonyms

Abstract

Words that are homonyms-that is, for which a single written and spoken form is associated with multiple, unrelated interpretations, such as COMPOUND, which can denote an <enclosure> or a <composite> meaning-are an invaluable class of items for studying word and discourse comprehension. When using homonyms as stimuli, it is critical to control for the relative frequencies of each interpretation, because this variable can drastically alter the empirical effects of homonymy. Currently, the standard method for estimating these frequencies is based on the classification of free associates generated for a homonym, but this approach is both assumption-laden and resourcedemanding. Here, we outline an alternative norming methodology based on explicit ratings of the relative meaning frequencies of dictionary definitions. To evaluate this method, we collected and analyzed data in a norming study involving 544 English homonyms, using the eDom norming software that we developed for this purpose. Dictionary definitions were generally sufficient to exhaustively cover word meanings, and the methods converged on stable norms with fewer data and less effort on the part of the experimenter. The predictive validity of the norms was demonstrated in analyses of lexical decision data from the English Lexicon Project (Balota et al., Behavior Research Methods, 39, 445-459, 2007), and from Armstrong and Plaut (Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, [2223][2224][2225][2226][2227][2228] 2011). On the basis of these results, our norming method obviates relying on the unsubstantiated assumptions involved in estimating relative meaning frequencies on the basis of classification of free associates. Additional details of the norming procedure, the meaning frequency norms, and the source code, standalone binaries, and user manual for the software are available at http:// edom.cnbc.cmu.edu.Keywords Semantic ambiguity . Homonyms . Relative meaning frequency . Norming methods . Rating dictionary definitions . Free associate classification . Homonymy disadvantageThe vast majority of words in English and many other languages are semantically ambiguous-that is, they are associated with multiple distinct interpretations. For example, the word COMPOUND can denote either an <enclosure> or a <composite> meaning, depending on the context (hereafter denoted as <enclosure>/<composite> COMPOUND; Britton, 1978;Klein & Murphy, 2001). As a result, developing an account of semantic ambiguity resolution is a critical component of any theory of word and discourse comprehension, and this has been a key objective in a considerable body of research over the past several decades (e.g

Relative Meaning Frequencies for 100 Homonyms: British eDom Norms

“…One hundred words with the same spelling and pronunciation were selected from Armstrong, Tokowicz, & Plaut's norms [5]. Ninety-three of the words had two separate entries in the Wordsmyth dictionary [14], being suggestive of homonymy.…”

“…We followed the eDom procedure [5] very closely. Participants were instructed to estimate, as a percentage, how often each meaning of a homonym was implied when they encountered that word.…”

“…In the latter case, we added the frequency rating of such additional meanings (e.g., "mate" denoting a friend) to the frequency rating of the presented meaning ("mate" denoting a marriage partner). Unlike [5], we determined the semantic relatedness between the additional and presented meanings based on subjective ratings rather than entries in the Wordsmyth dictionary [14]. All 1,263 additional-meaning responses were coded independently by the first author (GM) and a linguist (EO) who was not involved in any other stages of the research.…”

“…To demonstrate that the present norming study was indeed warranted, we compared our British-English ratings to the analogous American-English ratings [5] for the first meaning of each homonym in the Wordsmyth dictionary [14]. This analysis was not initially possible due to different approaches to the categorisation of additional-meaning responses in the two norming studies.…”

“…Here, we provide the first meaning-frequency ratings in British English that were collected online using the eDom norming procedure [5]. This data set is essential to UK-based researchers examining ambiguity processing who must otherwise collect their own small-scale meaning-frequency ratings prior to experimental testing [e.g., 6,7,8] or use normative data in other dialects of English, despite recent evidence for dialectal differences in meaning frequency [9].…”