Many languages allow for “fake” uses of their past tense marker: the marker: can occur in certain contexts without conveying temporal pastness. Instead it appears to bear a modal meaning. Iatridou :231–270, 2000) has dubbed this phenomenon Fake Tense. Fake Tense is particularly common to conditional constructions. This paper analyzes Fake Tense in English conditional sentences as a certain kind of ambiguity: the past tense morphology can mark the presence of a temporal operator, but it can also (...) signal a specific modal operator. The ambiguity is proposed to be the result of recategorization: the Simple Past develops a second, modal meaning because of structural similarities between the temporal and the modal/epistemic domain. The proposal is spelled out in the generative semantics framework, using the restrictor approach to conditionals Semantics from different points of view, 1979; in: A. von Stechow and D. Wunderlich Semantics: an international handbook of contemporary research, 1991), and building on von Stechows et al.’s recent work on the English tense system The expression of time in language, 2010; Romero and von Stechow, Tense: introduction, 2008). (shrink)

This study is concerned with the properties of the disjunction operator, or, and the acquisition of these properties by English-speaking children. Previous research has concluded that adult truth conditions for logical connectives are acquired relatively late in the course of language development. With particular reference to disjunction, the results of several studies have led to two claims. First, it has been argued that the full range of truth-conditions associated with inclusive-or is not initially available to children; instead, children are supposed (...) to interpret disjunction using the truth conditions that are associated with exclusive-or (e.g., Beilin and Lust 1975; Braine and Rumain 1981, 1983; Paris 1973). A second, related claim is that even when children respond as if they have access to the complete range of truth conditions, their responses result from the failure to distinguish or from and (Paris, 1973). (shrink)

This study is concerned with the properties of the disjunction operator, or, and the acquisition of these properties by English-speaking children. Previous research has concluded that adult truth conditions for logical connectives are acquired relatively late in the course of language development. With particular reference to disjunction, the results of several studies have led to two claims. First, it has been argued that the full range of truth-conditions associated with inclusive-or is not initially available to children; instead, children are supposed (...) to interpret disjunction using the truth conditions that are associated with exclusive-or (e.g., Beilin and Lust 1975; Braine and Rumain 1981, 1983; Paris 1973). A second, related claim is that even when children respond as if they have access to the complete range of truth conditions, their responses result from the failure to distinguish or from and (Paris, 1973). Different conclusions were reached in recent work by Chierchia, Crain, Guasti and Thornton (1998). The experiments conducted by Chierchia et al. (1998) draw upon a distinction between linguistic contexts. In one type of context, the inclusive-or reading of disjunction is available. By contrast, in another type of context, the exclusive-or reading of disjunction is highly preferred; the truth conditions that are uniquely associated with the inclusive-or reading are eliminated in such contexts due to conversational implicatures. One context that cancels conversational implicatures is called the Prediction Mode by Chierchia et al. (1998). Notice that a prediction like (1) is consistent with different scenarios. (shrink)

According to mental model theory, illusory inferences are a class of deductions in which individuals systematically go wrong. Mental model theory explains them invoking the principle of truth, which is a tendency not to represent models that falsify the premises. In this paper we focus on the illusory problems based on conditional sentences. In three experiments, we show that: (a) rather than not representing models that falsify the conditionals, participants have a different understanding of what falsifies a (...) class='Hi'>conditional (Experiment I); (b) specifically, participants think that a conditional with an impossible antecedent or consequent is false (Experiment 2); (c) if the domain of the conditionals in the illusory problems are expanded to show that their antecedents and consequents are possible, the participants find it easy to reach the correct conclusions (Experiment 3). According to our results, the illusory inferences based on conditional premises, differently from those based on disjunctive premises, are caused by a difference between the understanding of natural language factual conditionals and the truth table of the factual implication; the principle of truth is not necessary to explain them. (shrink)

Quentin Smith has argued that the new tenseless theory of time is faced with insurmountable problems and should be abandoned in favour of the tensed theory of time. Smith;s main argument attacks the fundamental premise of the tenseless theory: that tenseless truth conditions for tokens of tensed sentences adequately capture the meaning of tensed sentences. His position is that tenseless truth conditions cannot explain the logical relations between tensed sentences, thus the tensed theory must be accepted. Against (...) Smith, this paper adopts an alternative approach to the explanation of the entailment relations between sentences which contain indexicals. The approach drops the reliance upon tokens and instead relies on the evaluation of sentence types with respect to a context rather than upon actual or possible utterances of tokens of the types. This (new) version of the tenseless theory of time can adequately explain the relevant entailment relations between tensed sentences. (shrink)

This paper is about what we may provisionally call “indicative” conditionals. It aims to describe one use of the word ‘if’, by giving the truth conditions of sentences using ‘if’ in the way in question. Here are some sentences that, on their natural interpretations, illustrate the target use.

We give a procedure to obtain falsity conditions for IF-sentences, using Skolemization. The expressive power of an IF-sentence can then be strongly captured by a pair of Σ11-sentences. A result from [Burgess 2003] shows that, conversely, any pair of incompatible Σ11-sentences corresponds with an IF-sentence.In the second part, we reflect on the influence of the order of the steps (inside-out versus outside-in) in the Skolemization procedures for IF-logic. We also reflect on the nature of game theoretical negation.

We give a procedure to obtain falsity conditions for IF-sentences, using Skolemization. The expressive power of an IF-sentence can then be strongly captured by a pair of Σ11-sentences. A result from [Burgess 2003] shows that, conversely, any pair of incompatible Σ11-sentences corresponds with an IF-sentence.In the second part, we reflect on the influence of the order of the steps (inside-out versus outside-in) in the Skolemization procedures for IF-logic. We also reflect on the nature of game theoretical negation.

This paper is about what we may provisionally call “indicative” conditionals. It aims to describe one use of the word ‘if’, by giving the truth conditions of sentences using ‘if’ in the way in question. Here are some sentences that, on their natural interpretations, illustrate the target use.

The presence of predictive AI has steadily expanded into ever-increasing aspects of civil society. I aim to show that despite reasons for believing the use of such systems is currently problematic, these worries give no indication of their future potential. I argue that the absence of moral limits on how we might manipulate automated systems, together with the likelihood that they are more easily manipulated in the relevant ways than humans, suggests that such systems will eventually outstrip the human ability (...) to make accurate judgments and unbiased predictions. I begin with some reasonable justifications for the use of predictive AI. I then discuss two of the most significant reasons for believing the use of such systems is currently problematic before arguing that neither provides sufficient reason against such systems being superior in the future. In fact, there’s reason to believe they can, in principle, be preferable to human decision makers. (shrink)

It has been proposed that the ways in which the criminal justice system treats offenders with Autism spectrum condition should duly account for how the condition influences the offenders’ behavior. While the recommendation appears plausible, what adhering to it means in practice remains unclear. A central feature of ASC is seen to be that people with the condition have difficulties with understanding and reacting to the mental states of others in what are commonly considered as adequate ways. This article aims (...) to clarify how the difficulties affect the moral weight to be given to the good and bad motives of offending in sentencing offenders with ASC. I start by explicating the main points of departure of the endeavor. After that I assess the moral significance of the good and bad motives of offenders with ASC in view of four cases and a comparison with how we commonly treat people who are not as able to understand and react to the mental states of others as neurotypical adults. I suggest that considerations pertaining to what has been called the primary orientation of morality provide grounds for deeming the good motives of offenders with ASC as morally significant as those of otherwise similar neurotypical offenders and the bad motives of offenders with ASC as less morally significant than those of otherwise similar neurotypical offenders. After considering three possible objections to the suggestion, I conclude by briefly elucidating its purported import. (shrink)

Mandy Simons. On The Felicity Conditions of Disjunctive Sentences.

The determination argument is supposed to show that a sentence's meaning is at least a truth‐condition. This argument is supposed to rest on innocent premises that even a deflationist about truth can accept. The argument comes in two versions: one is metaphysical and the other is epistemological. In this paper we will focus on the epistemological version. We will argue that the apparently innocent first premise of that version of the argument is not as innocent as it seems. If the (...) premise is understood in the sense required for the argument to go through then it should be rejected by a deflationist. (shrink)

The determination argument is supposed to show that a sentence's meaning is at least a truth-condition. This argument is supposed to rest on innocent premises that even a deflationist about truth can accept. The argument comes in two versions: one is metaphysical and the other is epistemological. In this paper we will focus on the epistemological version. We will argue that the apparently innocent first premise of that version of the argument is not as innocent as it seems. If the (...) premise is understood in the sense required for the argument to go through then it should be rejected by a deflationist. (shrink)

Sentence boundary detection (SBD) represents an important first step in natural language processing since accurately identifying sentence boundaries significantly impacts downstream applications. Nevertheless, detecting sentence boundaries within legal texts poses a unique and challenging problem due to their distinct structural and linguistic features. Our approach utilizes deep learning models to leverage delimiter and surrounding context information as input, enabling precise detection of sentence boundaries in English legal texts. We evaluate various deep learning models, including domain-specific transformer models like LegalBERT and (...) CaseLawBERT. To assess the efficacy of our deep learning models, we compare them with a state-of-the-art domain-specific statistical conditional random field (CRF) model. After considering model size, F1-score, and inference time, we identify the Convolutional Neural Network Model (CNN) as the top-performing deep learning model. To further enhance performance, we integrate the features of the CNN model into the subsequent CRF model, creating a hybrid architecture that combines the strengths of both models. Our experiments demonstrate that the hybrid model outperforms the baseline model, achieving a 4% improvement in the F1-score. Additional experiments showcase the superiority of the hybrid model over SBD open-source libraries when confronted with an out-of-domain test set. These findings underscore the importance of efficient SBD in legal texts and emphasize the advantages of employing deep learning models and hybrid architectures to achieve optimal performance. (shrink)

We propose a new approach to conditional donkey sentences that allows us to face successfully the often called proportion problem. The main ingredients of the proposal are van Benthem's generalized quantifier approach to conditionals, and Barwise's situation semantics. We present some experimental data supporting our proposal.

Modus ponens is the argument from premises of the form If A, then B and A to the conclusion B. Nearly all participants agree that the modus ponens conclusion logically follows when the argument appears in this Basic form. However, adding a further premise can lower participants’ rate of agreement—an effect called suppression. We propose a theory of suppression that draws on contemporary ideas about conditional sentences in linguistics and philosophy. Semantically, the theory assumes that people interpret an (...) indicative conditional as a context-sensitive strict conditional: true if and only if its consequent is true in each of a contextually determined set of situations in which its antecedent is true. Pragmatically, the theory claims that context changes in response to new assertions, including new conditional premises. Thus, the conclusion of a modus ponens argument may no longer be accepted in the changed context. Psychologically, the theory describes people as capable of reasoning about broad classes of possible situations, ordered by typicality, without having to reason about individual possible worlds. The theory accounts for the main suppression phenomena, and it generates some novel predictions that new experiments confirm. (shrink)

Conditional sentences are among the most intriguing and puzzling features of language, and analysis of their meaning and function has important implications for, and uses in, many areas of philosophy. Jonathan Bennett, one of the world's leading experts, distils many years' work and teaching into this Philosophical Guide to Conditionals, the fullest and most authoritative treatment of the subject. An ideal introduction for undergraduates with a philosophical grounding, it also offers a rich source of illumination and stimulation for (...) graduate students and professional philosophers. (shrink)

In response to the racial disparities that plague the American criminal justice system, the Movement for Black Lives calls for an end to policing and punishment “as we know it.” But refusing to punish violent offenses leaves unprotected those most vulnerable to crime, and outright abolition thus appears to undermine black rights and liberties. I call this the decarceration dilemma. After discussing Tommie Shelby and Christopher Lewis’s attempts to resolve the dilemma, I offer my own, which employs a procedural rather (...) than a substantive solution. I lean on the principle of expanded asymmetry (EA), which holds that it is better to underpunish than overpunish. After defending EA, I note that it obtains only under conditions of uncertainty. I then show that because virtually all trials of black offenders meet the uncertainty condition, sentencing authorities are obliged to treat black offenders leniently. I conclude by noting the advantages of my proceduralist approach. (shrink)

To avoid post-neurosurgical language deficits, intraoperative mapping of the language function in the brain can be complemented with preoperative mapping with functional magnetic resonance imaging. The validity of an fMRI “language localizer” paradigm crucially depends on the choice of an optimal language task and baseline condition. This study presents a new fMRI “language localizer” in Russian using overt sentence completion, a task that comprehensively engages the language function by involving both production and comprehension at the word and sentence level. The (...) paradigm was validated in 18 neurologically healthy volunteers who participated in two scanning sessions, for estimating test–retest reliability. For the first time, two baseline conditions for the sentence completion task were compared. At the group level, the paradigm significantly activated both anterior and posterior language-related regions. Individual-level analysis showed that activation was elicited most consistently in the inferior frontal regions, followed by posterior temporal regions and the angular gyrus. Test–retest reliability of activation location, as measured by Dice coefficients, was moderate and thus comparable to previous studies. Test–retest reliability was higher in the frontal than temporo-parietal region and with the most liberal statistical thresholding compared to two more conservative thresholding methods. Lateralization indices were expectedly left-hemispheric, with greater lateralization in the frontal than temporo-parietal region, and showed moderate test-retest reliability. Finally, the pseudoword baseline elicited more extensive and more reliable activation, although the syllable baseline appears more feasible for future clinical use. Overall, the study demonstrated the validity and reliability of the sentence completion task for mapping the language function in the brain. The paradigm needs further validation in a clinical sample of neurosurgical patients. Additionally, the study contributes to general evidence on test–retest reliability of fMRI. (shrink)

Conditional sentences are among the most intriguing and puzzling features of language, and analysis of their meaning and function has important implications for, and uses in, many areas of philosophy. Jonathan Bennett, one of the world's leading experts, distils many years' work and teaching into this book, making it the fullest and most authoritative treatment of the subject.

Conditional learning, where agents learn a conditional sentence ‘If A, then B,’ is difficult to incorporate into existing Bayesian models of learning. This is because conditional learning is not uniform: in some cases, learning a conditional requires decreasing the probability of the antecedent, while in other cases, the antecedent probability stays constant or increases. I argue that how one learns a conditional depends on the causal structure relating the antecedent and the consequent, leading to a (...) causal model of conditional learning. This model extends traditional Bayesian learning by incorporating causal models into agents’ epistemic states. On this theory, conditional learning proceeds in two steps. First, an agent learns a new causal model with the appropriate relationship between the antecedent and the consequent. Then, the agent narrows down the set of possible worlds to include only those which make the conditional proposition true. This model of learning can incorporate both standard cases of Bayesian learning and the non-uniform learning required to learn conditional information. (shrink)

Philosophers investigating the interpretation and use of conditional sentences have long been intrigued by the intuitive correspondence between the probability of a conditional `if A, then C' and the conditional probability of C, given A. Attempts to account for this intuition within a general probabilistic theory of belief, meaning and use have been plagued by a danger of trivialization, which has proven to be remarkably recalcitrant and absorbed much of the creative effort in the area. But (...) there is a strategy for avoiding triviality that has been known for almost as long as the triviality results themselves. What is lacking is a straightforward integration of this approach in a larger framework of belief representation and dynamics. This paper discusses some of the issues involved and proposes an account of belief update by conditionalization. (shrink)

This paper develops a trivalent semantics for indicative conditionals and extends it to a probabilistic theory of valid inference and inductive learning with conditionals. On this account, (i) all complex conditionals can be rephrased as simple conditionals, connecting our account to Adams's theory of p-valid inference; (ii) we obtain Stalnaker's Thesis as a theorem while avoiding the well-known triviality results; (iii) we generalize Bayesian conditionalization to an updating principle for conditional sentences. The final result is a unified semantic (...) and probabilistic theory of conditionals with attractive results and predictions. (shrink)