Good communication is vital in healthcare both among healthcare professionals and be tween healthcare professionals and their patients And well written documents describing and or explaining the information in structured databases may be easier to comprehend more edifying and even more convincing than the structured data even when presented in tabu lar or graphic form Documents may be automatically generated from structured data using techniques from the eld of natural language generation These techniques are concerned with how the (...) content organisation and language used in a document can be dynamically selected depending on the audience and context They have been used to generate health education ma terials explanations and critiques in decision support systems and medical reports and progress notes.. (shrink)

This article presents an architecture for natural language generation of biomedical argumentation. The goal is to reconstruct the normative arguments that a domain expert would provide, in a manner that is transparent to a lay audience. Transparency means that an argument's structure and functional components are accessible to its audience. Transparency is necessary before an audience can fully comprehend, evaluate or challenge an argument, or re-evaluate it in light of new findings about the case or changes in scientific (...) knowledge. The architecture has been implemented and evaluated in the Genetics Information Expression Assistant, a prototype system for drafting genetic counselling patient letters. Argument generation makes use of abstract argumentation schemes. Derived from the analysis of arguments used in genetic counselling, these mainly causal argument patterns refer to abstract properties of qualitative causal domain models. (shrink)

This paper asks why information should ever be expressed vaguely, re-assessing some previously proposed answers to this question and suggesting some new ones. Particular attention is paid to the benefits that vague expressions can have in situations where agreement over the meaning of an expression cannot be taken for granted. A distinction between two different versions of the above-mentioned question is advocated. The first asks why human languages contain vague expressions, the second question asks when and why a speaker should (...) choose a vague expression when communicating with a hearer. While the former question is purely theoretical, the latter has practical implications for the computational generation of utterances in Natural Language Generation (NLG). (shrink)

This paper asks why information should ever be expressed vaguely, re-assessing some previously proposed answers to this question and suggesting some new ones. Particular attention is paid to the benefits that vague expressions can have in situations where agreement over the meaning of an expression cannot be taken for granted. A distinction between two different versions of the above-mentioned question is advocated. The first asks why human languages contain vague expressions, the second question asks when and why a speaker should (...) choose a vague expression when communicating with a hearer. While the former question is purely theoretical, the latter has practical implications for the computational generation of utterances in Natural Language Generation (NLG). (shrink)

This informal position paper brings together some recent developments in formal semantics and pragmatics to argue that the discipline of Game Theory is well placed to become the theoretical backbone of Natural Language Generation. To demonstrate some of the strengths and weaknesses of the Game-Theoretical approach, we focus on the utility of vague expressions. More specifically, we ask what light Game Theory can shed on the question when an NLG system should generate vague language.

Algorithms for NLG NLG is typically broken down into stages of discourse planning (to select information and organize it into coherent paragraphs), sentence planning (to choose words and structures to fit information into sentence-sized units), and realization (to determine surface form of output, including word order, morphology and final formatting or intonation). The SPUD system combines the generation steps of sentence planning and surface realization by using a lexicalized grammar to construct the syntax and semantics of a sentence simultaneously.

Syllogism is a type of everyday reasoning. For instance, given that ‘Avicenna wrote the famous book the Canon of Medicine’ and ‘The Canon of Medicine has influenced modern medicine,’ it can be conc...

In trying to control various aspects concerning utterance production in multi-party human–computer dialogue, argumentative considerations play an important part, particularly in choosing appropriate lexical units so that we fine-tune the degree of persuasion that each utterance has. A preliminary step in this endeavor is the ability to place an ordering relation between semantic forms (that are due to be realized as utterances, by the machine), concerning their persuasion strength, with respect to certain (explicit or implicit) conclusions. Thus, in this article, (...) we propose a mechanism for assessing utterances, in terms of their argumentative force. The framework designed conflates insights from Asher and Lascarides’ SDRT (“Segmented Discourse Representation Theory”), and from Anscombre and Ducrot’s AT (“Argumentation Theory”). These mechanisms are included in a language generation component of a multi-party dialogue system for book reservation applications (i.e., a “virtual librarian”), and thus evaluated via typical human–machine conversations. (shrink)

This book introduces the concept of information sharing as an area of cognitive science, defining it as the process by which speakers depend on "given" information to convey "new" information—an idea crucial to language engineering. Where previous work in information sharing was often fragmented between different disciplines, this volume brings together theoretical and applied work, and joins computational contributions with papers based on analyses of language corpora and on psycholinguistic experimentation.

[ https://plus.google.com/108060242686103906748/posts/cwvdB6mK3J6 ]"As Literature germinates within me, my words are-“Literature is something, that I need to be acclaimed for, I need to know more...it’s my life that has given me birth, my way of thoughts that I am visualizing in the perspective of all dimensions, my frailties, my faults...my every comprehensive discussion even after my death, my spiritualism, my haunting towards the ecology of the cosmic world, and the way that I have brought up at my elbows to enhance myself (...) more in the bloom of dissolved doomed tragedy of a human life! It is indeed ravenous…but we the beings to run through this midst of life, as I need to pace up with at every inception and the idealistic phenomenal moments…!”. . (http://philpapers.org/profile/112741.). (shrink)

The aim of the current research is to investigate the feasibility of identifying offensive language in Lithuanian by utilising the Simplified Offensive Language Taxonomy (SOLT). The key principle behind this taxonomy is its ability to complement existing offensive language ontologies and tagset systems, with the ultimate goal of integrating it into publicly accessible Linguistic Linked Open Data (LLOD) resources. The dataset used in the current study is a publicly available corpus of user-generated comments collected from a Lithuanian (...) portal (Amilevičius et al. 2016). The study identified that offensive language predominantly focuses on collective derogatory language rather than individuals. The most common category of offensive language is related to physical and mental disabilities, followed by ideological offenses, xenophobic and sexist remarks, and less frequent categories like ageism, classism, homophobia, and religious discrimination. These results highlight the diverse range of offensive language online and underscore the need to combat discrimination and promote respectful discourse, particularly concerning marginalised groups. (shrink)

Philosophers have hitherto only interpreted the world in various ways; the point is to change it.Karl marx’s distinction between interpreting the world and changing it points by extension to the state of contemporary philosophy and psychiatry. The 1990s resurgence of interdisciplinary work in this area was driven equally by phenomenological scholarship and by initiatives in analytic philosophy. The former reflected the focus in phenomenology on ‘what it is like’ to experience a given mental symptom with the aim of reconstructing the (...) life-worlds of people experiencing mental disorders, while the latter reflected directly or indirectly the influence of J. L. Austin and others from... (shrink)

An analysis of Mark Bevir's account of the role of language and tradition on the one hand, and the individual on the other in the generation of ideas, and proposal of an alternative account It endorses Bevir's project of finding a middle way between individualism and collectivism, but finds that Bevir exaggerates the role of the individual. It argues that human selves always remains dependent on language even to articulate their own intentions to themselves. Whilst they have (...) a capacity to create new linguistic expressions, this is always limited to the exploration of possibilities already latent in the language. However, no one is a mere recipient and conduit of a given language: everyone hands it on transformed by their unique appropriation of it. The antifoundationalist analyses of Wittgenstein, Newman Collingwood, and Neurath are invoked to argue that this state of affairs also applies to the individual's relation to the beliefs and values inherited traditionally: there is no possibility of a wholesale rejection of what is received; no individual can reject all received traditions, and erect an entire belief structure from scratch, but can only modify it on a piecemeal basis, so that received tradition always remains constitutive of the individual mind. It is also argued that human self-consciousness is always socially formed, and no person ever completely integrated, and stabilized. No one is ever therefore in a state of complete self-possession. One therefore must reject Bevir's claim that the historian of ideas must initially presume that individuals are sincere, conscious and rational in their expressed beliefs: ‘sincere’ self-consciousness is an ideal never fully achieved, and beliefs as to what constitutes ‘rationality’ are so varied that specific presumptions cannot be made. (shrink)

Automated software engineering has attracted a large amount of research efforts. The use of object-oriented methods for software systems development has made it necessary to develop approaches that automate the construction of different Unified Modeling Language models in a semiautomated approach from textual user requirements. UML use case models represent an essential artifact that provides a perspective of the system under analysis or development. The development of such use case models is very crucial in an object-oriented development method. The (...) main principles used in obtaining these models are described. A natural language processing tool is used to parse different statements of the user requirements written in Arabic to obtain lists of nouns, noun phrases, verbs, verb phrases, etc., that aid in finding potential actors and use cases. A set of steps that represent our approach for constructing a use case model are presented. Finally, the proposed approach is validated using an experiment involving a group of graduate students who are familiar with use case modeling. (shrink)

��We describe a comprehensive framework for text un- derstanding, based on the representation of context. It is designed to serve as a representation of semantics for the full range of in- terpretive and inferential needs of general natural language pro- cessing. Its most distinctive feature is its uniform representation of the various simple and independent linguistic sources that play a role in determining meaning: lexical associations, syntactic re- strictions, case-role expectations, and most importantly, contextual effects. Compositional syntactic structure from (...) a shallow parsing is represented in a neural net-based associative memory, where it then interacts through a Bayesian network with semantic associa- tions and the context or “gist” of the passage carried forward from preceding sentences. Experiments with more than 2000 sentences in different languages are included. (shrink)

In this article, I investigate to what extent future generations that belong to language minorities are entitled to group rights that protect their linguistic identity. In particular, I assess whether these future generations are entitled to assistance rights, symbolic claims, self-government rights and exemptions from the law. To address this I outline three arguments supporting group rights for current generations and raise the question of whether these arguments, which are true for current generations, will also be true for future (...) generations. The answer defends the entitlement of future generations to group rights against two counterarguments. The first is that future generations have no interest in preserving their language and therefore there is no normative justification for group rights. The second is that there is a duty to eliminate group rights in order to avoid malign consequences of these rights for future generations. (shrink)

We describe a comprehensive framework for text un- derstanding, based on the representation of context. It is designed..

A substantial amount of recent work in natural language generation has focused on the generation of ‘‘one‐shot’’ referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It (...) turns out that the success of the IA depends substantially on the ‘‘preference order’’ (PO) employed by the IA, particularly in complex domains. While some POs cause the IA to produce referring expressions that are very similar to expressions produced by human subjects, others cause the IA to perform worse than its main competitors; moreover, it turns out to be difficult to predict the success of a PO on the basis of existing psycholinguistic findings or frequencies in corpora. We also examine the computational complexity of the algorithms in question and argue that there are no compelling reasons for preferring the IA over some of its main competitors on these grounds. We conclude that future research on the generation of referring expressions should explore alternatives to the IA, focusing on algorithms, inspired by the Greedy Algorithm, which do not work with a fixed PO. (shrink)

Human beings express affinity (Shinwa‐kan in Japanese language) in communicating transactive engagements among healthcare providers, patients and healthcare robots. The appearance of healthcare robots and their language capabilities often feature characteristic and appropriate compassionate dialogical functions in human–robot interactions. Elements of healthcare robot configurations comprising its physiognomy and communication properties are founded on the positivist philosophical perspective of being the summation of composite parts, thereby mimicking human persons. This article reviews Mori's theory of the Uncanny Valley and its (...) consequent debates, and examines "Uncanny" relations with generating healthcare robot conversational content with artificial affective communication (AAC) using natural language processing. With healthcare robots provoking influential physical composition and sensory expressions, the relations in human–healthcare robot transactive engagements are argued as supportive of the design and development in natural language processing. This implies that maintaining human–healthcare robot interaction and assessing the eeriness situations explained in the Uncanny Valley theory are crucial positions for healthcare robot functioning as a valuable commodity in health care. As such, physical features, language capabilities and mobility of healthcare robots establish the primacy of the AAC with natural language processing as integral to healthcare robot–human healthcare practice. (shrink)

This chapter examines the role played by derogatory terms (e.g., ‘inyenzi’ or cockroach, ‘inzoka’ or snake) in laying the social groundwork for the genocide of the Tutsi in Rwanda in 1994. The genocide was preceded by an increase in the use of anti-Tutsi derogatory terms among the Hutu. As these linguistic practices evolved, the terms became more openly and directly aimed at Tutsi. Then, during the 100 days of the genocide, derogatory terms and coded euphemisms were used to direct killers (...) to their victims. Understanding these speech acts helps to illuminate the important ways that power is enacted through discourse, how speech acts can prepare the way for physical and material acts, and how speech generates permissions for actions hitherto uncountenanced. Studying the role of speech acts and linguistic practices in laying the groundwork of the genocide illuminates how patterns of speech acts become linguistic practices that constitute permissibility conditions for non-linguistic behaviors. Further, the analysis presented here helps to make sense of the view that a steady, deep, and widespread derogation of a group can be part and parcel of genocide, not only an antecedent to it. (shrink)

A substantial amount of recent work in natural language generation has focused on the generation of ‘‘one-shot’’ referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It (...) turns out that the success of the IA depends substantially on the ‘‘preference order’’ (PO) employed by the IA, particularly in complex domains. While some POs cause the IA to produce referring expressions that are very similar to expressions produced by human subjects, others cause the IA to perform worse than its main competitors; moreover, it turns out to be difficult to predict the success of a PO on the basis of existing psycholinguistic findings or frequencies in corpora. We also examine the computational complexity of the algorithms in question and argue that there are no compelling reasons for preferring the IA over some of its main competitors on these grounds. We conclude that future research on the generation of referring expressions should explore alternatives to the IA, focusing on algorithms, inspired by the Greedy Algorithm, which do not work with a fixed PO. (shrink)

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating syntactic objects. We argue that recently proposed principles of economy in language design—such as “minimal search” criteria from (...) theoretical syntax—adhere to the FEP. This affords a greater degree of explanatory power to the FEP—with respect to higher language functions—and offers linguistics a grounding in first principles with respect to computability. While we mostly focus on building new principled conceptual relations between syntax and the FEP, we also show through a sample of preliminary examples how both tree-geometric depth and a Kolmogorov complexity estimate (recruiting a Lempel–Ziv compression algorithm) can be used to accurately predict legal operations on syntactic workspaces, directly in line with formulations of variational free energy minimization. This is used to motivate a general principle of language design that we term Turing–Chomsky Compression (TCC). We use TCC to align concerns of linguists with the normative account of self-organization furnished by the FEP, by marshalling evidence from theoretical linguistics and psycholinguistics to ground core principles of efficient syntactic computation within active inference. (shrink)

En este artículo nos proponemos analizar las relaciones entre exilio, lengua y territorio en una lectura de poemas seleccionados de los libros Vicio de Miami (1997) y Confesiones del estrangulador de Flagler Street (1998), de Néstor Díaz de Villegas (Cienfuegos, Cuba, 1956). El eje propuesto pretende comprender, por un lado, algunos aspectos de su poética, como aparece en sus primeros libros publicados; por otro, ponerla en perspectiva respecto a la condición del exilio cubano en los Estados Unidos en la época (...) de la crisis de Mariel (1980), especialmente desde sus repercusiones en el campo de la cultura. (shrink)

A key requirement for the automatic generation of argumentative or explanatory text is to present the constituent propositions in an order that readers will find coherent and natural, to increase the likelihood that they will understand and accept the author’s claims. Natural language generation systems have standardly employed a repertoire of coherence relations such as those defined by Mann and Thompson’s Rhetorical Structure Theory. This paper models the generation of persuasive monologue as the outcome of an (...) “inner dialogue”, where the author attempts to anticipate potential challenges or clarification requests. It is argued that certain RST relations such as Motivate, Evidence and Concession can be seen to emerge from various pre-empting strategies. (shrink)

Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that language themselves. We analyze the consequences of iterated learning for learning algorithms based on the principles of Bayesian inference, assuming that learners compute a posterior distribution over languages by combining a prior (representing their inductive biases) with the evidence provided by linguistic data. We show that when learners sample (...) languages from this posterior distribution, iterated learning converges to a distribution over languages that is determined entirely by the prior. Under these conditions, iterated learning is a form of Gibbs sampling, a widely-used Markov chain Monte Carlo algorithm. The consequences of iterated learning are more complicated when learners choose the language with maximum posterior probability, being affected by both the prior of the learners and the amount of information transmitted between generations. We show that in this case, iterated learning corresponds to another statistical inference algorithm, a variant of the expectation-maximization (EM) algorithm. These results clarify the role of iterated learning in explanations of linguistic universals and provide a formal connection between constraints on language acquisition and the languages that come to be spoken, suggesting that information transmitted via iterated learning will ultimately come to mirror the minds of the learners. (shrink)

It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to derive from a language-specific biological endowment, which encodes universal, but communicatively arbitrary, principles of language structure (a Universal Grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes, resulting in a logical problem of language evolution. Specifically, as the processes (...) of language change are much more rapid than processes of genetic change, language constitutes a both over time and across different human populations, and, hence, cannot provide a stable environment to which language genes could have adapted. We conclude that a biologically determined UG is not evolutionarily viable. Instead, the original motivation for UG arises because language has been shaped to fit the human brain, rather than vice versa. Following Darwin, we view language itself as a complex and interdependent which evolves under selectional pressures from human learning and processing mechanisms. That is, languages themselves are shaped by severe selectional pressure from each generation of language users and learners. This suggests that apparently arbitrary aspects of linguistic structure may result from general learning and processing biases deriving from the structure of thought processes, perceptuo-motor factors, cognitive limitations, and pragmatics. (shrink)

(Near-final version.) Accepted for publication in Artificial Intelligence Journal.

This article explores the role of surface ambiguities in referring expressions, and how the risk of such ambiguities should be taken into account by an algorithm that generates referring expressions, if these expressions are to be optimally effective for a hearer. We focus on the ambiguities that arise when adjectives occur in coordinated structures. The central idea is to use statistical information about lexical co-occurrence to estimate which interpretation of a phrase is most likely for human readers, and to avoid (...) generating phrases where misunderstandings are likely. Various aspects of the problem were explored in three experiments in which responses by human participants provided evidence about which reading was most likely for certain phrases, which phrases were deemed most suitable for particular referents, and the speed at which various phrases were read. We found a preference for ‘‘clear’’ expressions to ‘‘unclear’’ ones, but if several of the expressions are ‘‘clear,’’ then brief expressions are preferred over non-brief ones even though the brief ones are syntactically ambiguous and the non-brief ones are not; the notion of clarity was made precise using Kilgarriff's Word Sketches. We outline an implemented algorithm that generates noun phrases conforming to our hypotheses. (shrink)