- Proceedings of the National Academy of Sciences of the United States of America
- Published almost 3 years ago
How universal is human conceptual structure? The way concepts are organized in the human brain may reflect distinct features of cultural, historical, and environmental background in addition to properties universal to human cognition. Semantics, or meaning expressed through language, provides indirect access to the underlying conceptual structure, but meaning is notoriously difficult to measure, let alone parameterize. Here, we provide an empirical measure of semantic proximity between concepts using cross-linguistic dictionaries to translate words to and from languages carefully selected to be representative of worldwide diversity. These translations reveal cases where a particular language uses a single “polysemous” word to express multiple concepts that another language represents using distinct words. We use the frequency of such polysemies linking two concepts as a measure of their semantic proximity and represent the pattern of these linkages by a weighted network. This network is highly structured: Certain concepts are far more prone to polysemy than others, and naturally interpretable clusters of closely related concepts emerge. Statistical analysis of the polysemies observed in a subset of the basic vocabulary shows that these structural properties are consistent across different language groups, and largely independent of geography, environment, and the presence or absence of a literary tradition. The methods developed here can be applied to any semantic domain to reveal the extent to which its conceptual structure is, similarly, a universal attribute of human cognition and language use.
Personalized medicine has recently become a main goal for healthcare policy. It is often defined as the tailoring of diagnosis and therapies to the genetic profile of each patient, and as such it is supposed to overcome the major thorny issues at stake in biomedicine today. This challenging program is primarily carried out by new approaches in biomedical imaging, molecular analysis, drug delivery and follow-up, taking more and more advantage of nanotechnology. However, in current literature and debates, the term ‘personalized medicine’ appears to be polysemous. The paper examines this polysemy. It links it to rival epistemic and technological choices in research programs, and it finally argues that this techno-epistemic plurality echoes conflicting expectations and values among today’s biomedicine actors.
Every word signifies multiple senses. Many studies using comprehension-based measures suggest that polysemes' senses (e.g., paper as in printer paper or term paper) share lexical representations, whereas homophones' meanings (e.g., pen as in ballpoint pen or pig pen) correspond to distinct lexical representations. Less is known about the lexical representations of polysemes compared to homophones in language production. In this study, speakers named pictures after reading sentence fragments that primed polysemes and homophones either as direct competitors to pictures (i.e., semantic-competitors), or as indirect-competitors to pictures (e.g., polysemous senses of semantic competitors, or homophonous meanings of semantic competitors). Polysemes (e.g., paper) elicited equal numbers of intrusions to picture names (e.g., cardboard) compared to in control conditions whether primed as direct competitors (printer paper) or as indirect-competitors (term paper). This contrasted with the finding that homophones (e.g., pen) elicited more intrusions to picture names (e.g., crayon) compared to in control conditions when primed as direct competitors (ballpoint pen) than when primed as indirect-competitors (pig pen). These results suggest that polysemes, unlike homophones, are stored and retrieved as unified lexical representations.
- Journal of experimental psychology. Learning, memory, and cognition
- Published over 2 years ago
The degree to which meanings are related in memory affects ambiguous word processing. We examined irregular polysemes, which have related senses based on similar or shared features rather than a relational rule, like regular polysemy. We tested to what degree the related meanings of irregular polysemes (wire) are represented with shared semantic information versus unshared information represented separately, like homonyms (bank). Monitoring eye fixations, we found that later context supporting the less frequent meaning of an irregular polyseme did not slow down reading compared with control conditions, whereas for homonyms it did. This indicates that in the absence of preceding biasing context, readers access a shared component of an irregular polyseme’s representation. Additionally, when the same context words preceded the ambiguous word, both irregular polysemes and homonyms initially elicited longer reading times, but the observed reading slow-down was weaker and less persistent for irregular polysemes than homonyms, indicating less competition between meaning components. We interpret these results as evidence of a shared features representation for irregular polysemes, which additionally incorporates unshared portions of meaning that can compete. When preceding, biasing context is available, readers activate shared and unshared components of the senses, producing a more fully instantiated meaning. (PsycINFO Database Record
- Journal of experimental psychology. Human perception and performance
- Published almost 4 years ago
Semantic ambiguity has often been divided into 2 forms: homonymy, referring to words with 2 unrelated interpretations (e.g., bark), and polysemy, referring to words associated with a number of varying but semantically linked uses (e.g., twist). Typically, polysemous words are thought of as having a fixed number of discrete definitions, or “senses,” with each use of the word corresponding to one of its senses. In this study, we investigated an alternative conception of polysemy, based on the idea that polysemous variation in meaning is a continuous, graded phenomenon that occurs as a function of contextual variation in word usage. We quantified this contextual variation using semantic diversity (SemD), a corpus-based measure of the degree to which a particular word is used in a diverse set of linguistic contexts. In line with other approaches to polysemy, we found a reaction time (RT) advantage for high SemD words in lexical decision, which occurred for words of both high and low imageability. When participants made semantic relatedness decisions to word pairs, however, responses were slower to high SemD pairs, irrespective of whether these were related or unrelated. Again, this result emerged irrespective of the imageability of the word. The latter result diverges from previous findings using homonyms, in which ambiguity effects have only been found for related word pairs. We argue that participants were slower to respond to high SemD words because their high contextual variability resulted in noisy, underspecified semantic representations that were more difficult to compare with one another. We demonstrated this principle in a connectionist computational model that was trained to activate distributed semantic representations from orthographic inputs. Greater variability in the orthography-to-semantic mappings of high SemD words resulted in a lower degree of similarity for related pairs of this type. At the same time, the representations of high SemD unrelated pairs were less distinct from one another. In addition, the model demonstrated more rapid semantic activation for high SemD words, thought to underpin the processing advantage in lexical decision. These results support the view that polysemous variation in word meaning can be conceptualized in terms of graded variation in distributed semantic representations. (PsycINFO Database Record © 2015 APA, all rights reserved).
Theoretical linguistic accounts of lexical ambiguity distinguish between homonymy, where words that share a lexical form have unrelated meanings, and polysemy, where the meanings are related. The present study explored the psychological reality of this theoretical assumption by asking whether there is evidence that homonyms and polysemes are represented and processed differently in the brain. We investigated the time-course of meaning activation of different types of ambiguous words using EEG. Homonyms and polysemes were each further subdivided into two: unbalanced homonyms (e.g., “coach”) and balanced homonyms (e.g., “match”); metaphorical polysemes (e.g., “mouth”) and metonymic polysemes (e.g., “rabbit”). These four types of ambiguous words were presented as primes in a visual single-word priming delayed lexical decision task employing a long ISI (750ms). Targets were related to one of the meanings of the primes, or were unrelated. ERPs formed relative to the target onset indicated that the theoretical distinction between homonymy and polysemy was reflected in the N400 brain response. For targets following homonymous primes (both unbalanced and balanced), no effects survived at this long ISI indicating that both meanings of the prime had already decayed. On the other hand, for polysemous primes (both metaphorical and metonymic), activation was observed for both dominant and subordinate senses. The observed processing differences between homonymy and polysemy provide evidence in support of differential neuro-cognitive representations for the two types of ambiguity. We argue that the polysemous senses act collaboratively to strengthen the representation, facilitating maintenance, while the competitive nature of homonymous meanings leads to decay.
Words mean different things in different contexts, a phenomenon called polysemy. People talk about lines of both people and poetry, and about both long distances and long times. Polysemy lets a limited vocabulary capture a great variety of experiences, while highlighting commonalities. But how is this achieved? Are polysemous senses contextually driven modifications of core meanings, or must each sense be memorized separately? We show that participants' ability to avoid referentially ambiguous descriptions of pictures named by polysemous words provides evidence for both possibilities. When senses followed a regular pattern (e.g., animals and the foodstuffs derived from them; noisy chicken, tasty chicken), participants avoided using ambiguous labels in referentially ambiguous situations (e.g., both types of chicken were present), a result indicating that they noticed a common meaning. But when senses were idiosyncratically related (e.g., sheet of glass, drinking glass), participants frequently produced ambiguous labels, a result indicating that the meanings were separately stored. We discuss implications for the relationship between word meanings and concepts.
Semantic ambiguity is typically measured by summing the number of senses or dictionary definitions that a word has. Such measures are somewhat subjective and may not adequately capture the full extent of variation in word meaning, particularly for polysemous words that can be used in many different ways, with subtle shifts in meaning. Here, we describe an alternative, computationally derived measure of ambiguity based on the proposal that the meanings of words vary continuously as a function of their contexts. On this view, words that appear in a wide range of contexts on diverse topics are more variable in meaning than those that appear in a restricted set of similar contexts. To quantify this variation, we performed latent semantic analysis on a large text corpus to estimate the semantic similarities of different linguistic contexts. From these estimates, we calculated the degree to which the different contexts associated with a given word vary in their meanings. We term this quantity a word’s semantic diversity (SemD). We suggest that this approach provides an objective way of quantifying the subtle, context-dependent variations in word meaning that are often present in language. We demonstrate that SemD is correlated with other measures of ambiguity and contextual variability, as well as with frequency and imageability. We also show that SemD is a strong predictor of performance in semantic judgments in healthy individuals and in patients with semantic deficits, accounting for unique variance beyond that of other predictors. SemD values for over 30,000 English words are provided as supplementary materials.
BACKGROUND: Ideally each Life Science article should get a ‘structured digital abstract’. This is a structured summary of the paper’s findings that is both human-verified and machine-readable. But articles can contain a large variety of information types and contextual details that all need to be reconciled with appropriate names, terms and identifiers, which poses a challenge to any curator. Current approaches mostly use tagging or limited entry-forms for semantic encoding. FINDINGS: We implemented a ‘controlled language’ as a more expressive representation method. We studied how usable this format was for wet-lab-biologists that volunteered as curators. We assessed some issues that arise with the usability of ontologies and other controlled vocabularies, for the encoding of structured information by ‘untrained’ curators. We take a user-oriented viewpoint, and make recommendations that may prove useful for creating a better curation environment: one that can engage a large community of volunteer curators. CONCLUSIONS: Entering information in a biocuration environment could improve in expressiveness and user-friendliness, if curators would be enabled to use synonymous and polysemous terms literally, whereby each term stays linked to an identifier.