Prior Beliefs Modulate Projection

Degen, Judith; Tonhauser, Judith

doi:10.1162/opmi_a_00042

Cited by 5 publications

(7 citation statements)

References 31 publications

(46 reference statements)

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“…Importantly, previous linguistic studies show that the projectivity of presupposition can vary depending on factors such as context, lexical items, prior beliefs, a speaker's social identity, and prosodic focus (Karttunen, 1971;Simons, 2001;Stevens et al, 2017;Tonhauser et al, 2018Degen and Tonhauser, 2021b). This variability is in line with the observation that humans make unsystematic judgments about projectivity on both natural (Ross and Pavlick, 2019; and controlled (White and Rawlins, 2018) sentences.…”

Section: Presupposition In Linguisticssupporting

confidence: 61%

“…Crucially, linguistic studies suggest that the projectivity can vary depending on many factors (Karttunen, 1971;Simons, 2001;Sevegnani et al, 2021;Tonhauser et al, 2018Degen and Tonhauser, 2021b). Previous probing studies in natural language processing examine models' performance on presuppositions in the natural language inference (NLI) task (Jeretic et al, 2020;Parrish et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments

Asami,

Sugawara

2023

Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)

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What makes a presupposition of an utteranceinformation taken for granted by its speakerdifferent from other pragmatic inferences such as an entailment is projectivity (e.g., the negative sentence the boy did not stop shedding tears presupposes the boy had shed tears before). The projectivity may vary depending on the combination of presupposition triggers and environments. However, prior natural language understanding studies fail to take it into account as they either use no human baseline or include only negation as an entailment-canceling environment to evaluate models' performance. The current study attempts to reconcile these issues. We introduce a new dataset, projectivity of presupposition (PROPRES), which includes 12k premise-hypothesis pairs crossing six triggers involving some lexical variety with five environments. Our human evaluation reveals that humans exhibit variable projectivity in some cases. However, the model evaluation shows that the best-performed model, DeBERTa, does not fully capture it. Our findings suggest that probing studies on pragmatic inferences should take extra care of the human judgment variability and the combination of linguistic items.

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Section: Presupposition In Linguisticssupporting

confidence: 61%

Section: Introductionmentioning

confidence: 99%

PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments

Asami,

Sugawara

2023

Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)

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“…In the case of news media, we would expect factive verbs to lead to stronger beliefs in headline claims, as their semantic properties predict. Nonetheless, a growing body of work has shown how contextual factors such as listeners’ prior beliefs and prosody can diminish the strength of factive entailments in conversation ( 22 , 23 ). These and other pragmatic factors specific to a media context could modulate the influence of factive framing on truth judgments for headlines as well.…”

Section: Epistemic Language Truth and Objectivitymentioning

confidence: 99%

Epistemic language in news headlines shapes readers’ perceptions of objectivity

Chuey,

Luo,

Markman

2024

Proc. Natl. Acad. Sci. U.S.A.

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How we reason about objectivity—whether an assertion has a ground truth—has implications for belief formation on wide-ranging topics. For example, if someone perceives climate change to be a matter of subjective opinion similar to the best movie genre, they may consider empirical claims about climate change as mere opinion and irrelevant to their beliefs. Here, we investigate whether the language employed by journalists might influence the perceived objectivity of news claims. Specifically, we ask whether factive verb framing (e.g., "Scientists know climate change is happening") increases perceived objectivity compared to nonfactive framing (e.g., "Scientists believe [...]"). Across eight studies (N = 2,785), participants read news headlines about unique, noncontroversial topics (studies 1a–b, 2a–b) or a familiar, controversial topic (climate change; studies 3a–b, 4a–b) and rated the truth and objectivity of the headlines’ claims. Across all eight studies, when claims were presented as beliefs (e.g., “Tortoise breeders believe tortoises are becoming more popular pets”), people consistently judged those claims as more subjective than claims presented as knowledge (e.g., “Tortoise breeders know…”), as well as claims presented as unattributed generics (e.g., “Tortoises are becoming more popular pets”). Surprisingly, verb framing had relatively little, inconsistent influence over participants’ judgments of the truth of claims. These results demonstrate how, apart from shaping whether we believe a claim is true or false, epistemic language in media can influence whether we believe a claim has an objective answer at all.

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“…Third, presupposition triggers exhibit gradience both in the sense that a listener may be more or less confdent about inferring what a speaker presupposes upon hearing different triggers (Tonhauser et al, 2018;Tonhauser and Degen, 2020;Degen and Tonhauser, 2021;Mahler, 2020), and in the sense that the presuppositions of different triggers may be more or less easy to cancel (Abusch, 2002;. Specifcally, some triggers are considered hard triggers, which require the presupposition to be satisfed for the statement to be well-formed.…”

Section: Introductionmentioning

confidence: 99%

NOPE: A Corpus of Naturally-Occurring Presuppositions in English

Parrish¹,

Schuster²,

Warstadt³

et al. 2021

Proceedings of the 25th Conference on Computational Natural Language Learning

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Understanding language requires grasping not only the overtly stated content, but also making inferences about things that were left unsaid. These inferences include presuppositions, a phenomenon by which a listener learns about new information through reasoning about what a speaker takes as given. Presuppositions require complex understanding of the lexical and syntactic properties that trigger them as well as the broader conversational context. In this work, we introduce the Naturally-Occurring Presuppositions in English (NOPE) Corpus to investigate the context-sensitivity of 10 different types of presupposition triggers and to evaluate machine learning models' ability to predict human inferences. We fnd that most of the triggers we investigate exhibit moderate variability. We further fnd that transformer-based models draw correct inferences in simple cases involving presuppositions, but they fail to capture the minority of exceptional cases in which human judgments reveal complex interactions between context and triggers.

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Prior Beliefs Modulate Projection

Cited by 5 publications

References 31 publications

PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments

PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments

Epistemic language in news headlines shapes readers’ perceptions of objectivity

NOPE: A Corpus of Naturally-Occurring Presuppositions in English

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