Antonymy and negation—The boundedness hypothesis

Paradis, Carita; Willners, Caroline

doi:10.1016/j.pragma.2005.11.009

Cited by 70 publications

(84 citation statements)

References 21 publications

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“…These results are in line with previous findings for English and Swedish by Paradis and Willners (2006) and Paradis et al (2009), who argue against the strict contrast between 'direct' and 'indirect' antonyms which has been assumed in the literature (see, for example, ) in favour of a scale of 'canonicity' where some word pairs are perceived as more antonymic than others. In particular, they propose that the weaker the degree of canonicity, the more different responses the target items will yield in an elicitation experiment.…”

Section: (C) Number Of (Different) Responses Across Word Classes and supporting

confidence: 92%

Proceedings of Workshop on Lexical and Grammatical Resources for Language Processing

Baptista¹,

Bhattacharyya

Fellbaum³

et al. 2014

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ii IntroductionThe first instance of the Workshop on Lexical and Grammatical Resources for Language Processing (LG-LP 2014) took place on August 24th in Dublin, in conjunction with COLING 2014. It was co-sponsored by ASIALEX and endorsed by SIGLEX.The workshop aimed to bring together members of the language-resource (LR) landscape, focusing on complex linguistic knowledge that requires linguistic expertise, e.g. on dictionaries, ontologies and grammars. Such manually-built resources are key to the development of natural language processing (NLP) tools and applications. We intended to strengthen the cohesion of the scientific 'production chain' spanning from the construction of LRs to their exploitation in hybrid or symbolic NLP. It is necessary to increase mutual awareness between researchers along this production chain, regarding their activities, skills and needs, in view of improving the building processes of the resources, their validation and their exploitation.Many linguists are comfortable with descriptive tasks such as checking lexical entries for a given feature, even if each entry requires analysing or pondering. On the other hand, computer scientists are familiar with formalization and, usually, with notions such as falsifiability or reproducibility, which are fundamental to sciences. Combining all these skills is likely to stimulate innovation. The workshop offered an opportunity of interaction which is required to overcome the compartmentalization between humanities and sciences, and to intensify co-operation between the two ends of the chain. Researchers were encouraged to exchange about how they manage to face several challenges:• the context of this production chain requires that they not be content with understanding phenomena, but also achieve actual production of formalized results;• resulting resources should reach a reasonable level of verifiability, e.g. by finding formal or syntactic bases as a support to semantic description;• methods which are able to cover the most diverse languages are to be preferred;• the format of manual construction of complex LRs must be highly readable, so that errors can be easily detected and corrected;• conceptual models are not easy to assign to large amounts of language data; due to idiosyncratic behaviour of lexical entries, it is often required to manually examine them individually as regards syntax or semantics;• many multiword expressions, including support-verb constructions, are somewhere halfway between compositional and non-compositional constructs;• actual implementation of NLP systems and real-world applications may provide feedback on complex lexical and grammatical LRs used in them, but experimentation is required to accurately relate features of the LRs with features of results obtained in NLP.We received 31 submissions and accepted 19: an acceptance rate of 61%. We scheduled 10 papers for oral presentation and 9 as posters. The workshop closed with a general discussion.We would like to thank the members of the Program Committee for their timely...

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Section: (C) Number Of (Different) Responses Across Word Classes and supporting

confidence: 92%

Proceedings of Workshop on Lexical and Grammatical Resources for Language Processing

Baptista¹,

Bhattacharyya

Fellbaum³

et al. 2014

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“…After all, why should one deny something unless this was in fact a possibility? The denial of criminality then (e.g., P is not a criminal) may itself prove incriminating (Wegner, et al, 1981;Wegner, Coulton & Wenzlaff, 1985; for related evidence see Christie et al 2001;Gilbert, Tafarodi & Malone, 1993;Gilbert, Krull & Malone, 1990;Grant, Malaviya, Sternthal, 2004;Hasson & Glucksberg, 2006;Kaup, Ludtke & Zwaan, 2006;Paradis &Willners, 2006). These findings demonstrate the consequences of using The negation bias 39 negations, rather than affirmations, in person description, and highlight the importance of the negation bias.…”

Section: Discussionmentioning

confidence: 99%

The negation bias: When negations signal stereotypic expectancies.

Beukeboom¹,

Finkenauer²,

Wigboldus³

2010

Journal of Personality and Social Psychology

108

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Research on linguistic biases shows that stereotypic expectancies are implicitly reflected in language and thereby subtly communicated to message recipients. We examined whether these findings extend to the use of negations (e.g., not smart instead of stupid). We hypothesized that people use more negations in descriptions of stereotype inconsistent behavior than in descriptions of stereotype consistent behavior. In three studies, participants either judged the applicability of experimentally controlled person descriptions, or spontaneously produced person descriptions themselves. Results provided support for this hypothesis. Moreover, a fourth study demonstrated that negations have communicative consequences. When a target person's behavior was described with negations, message recipients inferred that this behavior was an exception to the rule, and that it was more likely caused by situational circumstances than by dispositional factors. These findings indicate that by using negations people implicitly communicate stereotypic expectancies, and that negations play a subtle but powerful role in stereotype maintenance. The negation bias 3The Negation Bias: When Negations Signal Stereotypic ExpectanciesWhen people describe others' behaviors they can choose different words and formulations.For example, people can describe a person's dim comment as Harry was stupid or Harry was not smart. Which description they choose seems arbitrary at first sight. Both sentences adequately describe the event and people do not seem to give their choice of words muchthought. Yet, research shows that rather than being arbitrary, people's choice of words and language use is driven by systematic and implicit social cognitive processes. For instance, research on linguistic biases shows that people's prior expectancies and stereotypes influence their choice of words in describing others. That is, people use more abstract predicates to describe stereotype consistent behaviors than stereotype inconsistent behaviors. This biased language use not only reflects a speaker's stereotypic expectancies about a person, but, importantly, also transmits these expectancies to recipients. In this way, biased language use is one of the predominant means of stereotype maintenance at an interpersonal level (Maass, 1999;Maass, Salvi, Arcuri & Semin, 1989;Sekaquaptewa et al., 2003;Wigboldus, Semin & Spears, 2000).To extend our knowledge on linguistic biases, the present paper introduces the negation bias. Negation descriptions contain a negation marker such as not or no to deny the truth value of a particular proposition (e.g., Harry was not smart). We will refer to descriptions of others' behavior that include such negation markers as negations. Conversely, affirmation descriptions assert the truth value of a particular proposition and may be used to describe the same behavioral event (e.g., Harry was stupid). In the present research, we investigate whether the use of negations is influenced by people's stereotypic expectancies and whether negations...

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“…For instance, the majority of antonyms provided in a learner's dictionary are adjectives . Most of the pairings are gradable adjectives, either unbounded expressing a range on a scale such as good -bad, or bounded expressing a definite 'either-or' mode being able to express totality and partiality such as dead -alive (Paradis, 2001(Paradis, , 2008Paradis & Willners, 2006, but there are also non-gradable antonymous adjectives such as male -female.…”

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confidence: 99%

Good and bad opposites

Paradis

Willners

Jones

2009

Self Cite

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The goal of this paper is to combine corpus methodology with experimental methods to gain insights into the nature of antonymy as a lexico-semantic relation and the degree of antonymic canonicity of word pairs in language and in memory. Two approaches to antonymy in language are contrasted, the lexical categorical model and the cognitive prototype model. The results of the investigation support the latter model and show that different pairings have different levels of lexico-semantic affinity. At this general level of categorization, empirical methods converge; however, since they measure slightly different aspect of lexico-semantic opposability and affinity, and since the techniques of investigation are different in nature, we obtain slightly conflicting results at the more specific levels. We conclude that some antonym pairs can be diagnosed as "canonical" on the strength of three indicators: textual co-occurrence, individual judgement about "goodness" of opposition, and elicitation evidence.

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Antonymy and negation—The boundedness hypothesis

Cited by 70 publications

References 21 publications

Proceedings of Workshop on Lexical and Grammatical Resources for Language Processing

Proceedings of Workshop on Lexical and Grammatical Resources for Language Processing

The negation bias: When negations signal stereotypic expectancies.

Good and bad opposites

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