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OBJECTIVE Teaching and training surgeons work hard in the OR to understand each other, yet miscommunication is an important cause of preventable adverse events in surgery. Our objective was to perform a formal semantic analysis of language in authentic teaching surgical cases, identify the prevalence and typology of ambiguous or potentially ambiguous language, and describe their potential for miscommunication. DESIGN In this secondary analysis of qualitative data, we collaborated with a semanticist, categorizing linguistic phenomena often associated with miscommunication. We defined an ambiguous phenomenon as a string of language that could be reasonably interpreted in more than one way. We analyzed transcripts of 319 minutes of surgery, coding for 14 linguistic categories. Cohen's kappa was calculated. We determined the prevalence and rate of each linguistic category and chose illustrative examples. PARTICIPANTS AND SETTING Six surgical attendings, four fellows, and six residents, ranging from PGY1 to PGY4, at the University of Pittsburgh Medical Center, a tertiary medical center in Pittsburgh, Pennsylvania. RESULTS We found 3912 examples of potentially ambiguous language, 12.3 per minute. Percentage agreement between two expert raters was 76.3%. The most common phenomena were deixis (3.1 per minute), directional (2.6), anaphora (1.3), implicit instruction (1.3), and degree modifiers (0.7). Restatements/reframing occurred 1.4 times per minute. We identified 131 near misses associated with potentially ambiguous language. Cohen's kappa was 0.70 among expert semanticists. CONCLUSIONS Potentially ambiguous language is common and has the potential to jeopardize safe teaching surgery. We postulate that the high amount of potentially ambiguous language use in the operating room places a burden on the training surgeon to comprehend surgical instruction.

We construct a dynamic model of election campaigns. In the model, opportunities for candidates to refine/clarify their policy positions are limited and arrive stochastically along the course of the campaign until the predetermined election date. We show that this simple friction leads to rich and subtle campaign dynamics. We first demonstrate these effects in a series of canonical static models of elections that we extend to dynamic settings, including models with valence and a multidimensional policy space. We then present general principles that underlie the results from those models. In particular, we establish that candidates spend a long time using ambiguous language during the election campaign in equilibrium.

Recently entered into force, the administrative code was adopted with the stated purpose of unifying the regulations in the field of public administration, in order to create a normative framework, coming to the aid of individuals, public administration, but also of practitioners. In this respect, a significant part of the provisions were taken identically from the normative acts that were repealed, while there are also new provisions, some of them leaving, unfortunately, the impression of a code adopted in haste. Without claiming a thorough analysis of the entire regulation, the present study aims to address some of the challenges brought by the language used in OUG: 57/2019. Between the two extremes among which the legislator oscillates (either an incomplete or ambiguous language, or an over-regulation), the most relevant problem, in terms of the consequences that it can produce, probably consists in using already legally established notions, with a totally different meaning (such as, for example, the question of competence - exclusive, delegated or shared, or of the capacity or legal personality of public authorities). In addition to altering some already established rules or legal institutions, the code identifies in some places an unnecessary duplication of terms or the use of phrases that can completely change the meaning envisaged by the legislator; furthermore, the new normative act remains in debt (if it does not complicate matters even more) to clarify some problems previously identified by the scholars and the judicial practice (such as, of course, the role of the secretary in assessing the legality of the acts of the local public administration authorities or the majority necessary regarding the decisions related to the patrimony of the administrative-territorial unit).

The present essay examines seven aspects of the Gospel of John’s distinctive literary style which readers encounter often: solemn speech, ambiguous language, misunderstanding, irony, bridge verses,...

Contracts are agreements between parties engaging in economic transactions. They specify deontic modalities that the signatories should be held responsible for and state the penalties or actions to be taken if the stated agreements are not met. Additionally, contracts have also been known to be source of Software Engineering (SE) requirements. Identifying the deontic modalities in contracts can therefore add value to the Requirements Engineering (RE) phase of SE. The complex and ambiguous language of contracts make it difficult and time-consuming to identify the deontic modalities (obligations, permissions, prohibitions), embedded in the text. State-of-art neural network models are effective for text classification; however, they require substantial amounts of training data. The availability of contracts data is sparse owing to the confidentiality concerns of customers. In this paper, we leverage the linguistic and taxonomical similarities between regulations (available abundantly in the public domain) and contracts to demonstrate that it is possible to use regulations as training data for classifying deontic modalities in real-life contracts. We discuss the results of a range of experiments from the use of rule-based approach to Bidirectional Encoder Representations from Transformers (BERT) for automating the classification of deontic modalities. With BERT, we obtained an average precision and recall of 90% and 89.66% respectively.

International public health nutrition is an arm of international development that has recently gained visibility and traction. With growing numbers of actors involved, there are however multiple potential perspectives on what nutrition action means in practice. This empirical study aims to provide fresh insight and a stimulus to debate around research and practice in the world of international nutrition, exploring through literature review, interviews and political and social theory the questions: How has the discourse underpinning nutrition policy and practice evolved internationally over time; and how have changing narratives and interests affected the global agenda for nutrition? A dominant discourse in international nutrition currently is of the need for multi-sectoral action for the reduction of child stunting. The paper traces the evolution of this narrative through analysis of conflict among paradigms and among the actors that propagate them; the role of discursive strategies and framings as ‘strategically ambiguous’ to bring diverse actors together, though with sometimes contradictory actions in pursuit of a common stated goal; and the ‘rendering technical’ of complex, often politically-charged processes in order to more simply frame a response. There are practical implications of these divergent philosophies, ambiguous language, and contingent knowledge for the nutrition community and its actions to reduce the global burden of malnutrition. Problematizing nutrition issues in certain ways has implications for what is done to address them, so policy makers and practitioners should reflect on the limits that the ascendant paradigms, popular framings, and dominant forms of knowledge might impose on what may be done in their name.

Purpose Colleges and universities across the USA have seen data breaches and intellectual property theft rise at a heightened rate over the past several years. An integral step in the first line of defense against various forms of attacks are (written) security policies designed to prescribe the construction and function of a technical system, while simultaneously guiding the actions of individuals operating within said system. Unfortunately, policy analysis is an insufficiently discussed topic in many academic communities with very little research being conducted in this space. Design/methodology/approach This work aims to assess the current state of information security policies by analyzing in-use policies from 200 universities and colleges in the USA with the goal of identifying important features and general attributes of these documents. The authors accomplish this through a series of analyzes designed to examine the language and construction of these policies. Findings To summarize high-level results, the authors found that only 54 per cent of the top 200 universities had publicly accessible information security policies, and the policies that were examined lacked consistency with little shared source material. The authors also found that the tonal makeup of these policies lacked a great deal of emotion, but contained a high amount of tentative or ambiguous language leading toward policies that could be viewed as “unclear.” Originality/value This work is an extension of a paper that was presented at ECIS 2018. The authors have added additional analyzes including a cross-policy content and tonal analysis to strengthen the findings and implications of this work for the wider research audience.

The Chinese language has encouraged the paradigm shift in linguistics away from Chomsky-style sentence-internal rules toward usage-based discourse. Analysts have debated two possibilities: is Chinese an allegedly ‘inferior’ and ambiguous language because it rests on the ‘three zeros’: zero subjects, zero anaphora, and zero tense? Or does Chinese use ‘hidden complexity’ (Bisang 2009) to make reference clear by discourse marking? Chinese pressure points on linguistic theory center on these ‘three zeros’. Zero subjects have influenced a broader research category of topic-centered languages. Zero anaphora influenced reference tracking beyond the sentence. Zero tense expanded understanding of time and aspect. The process of the shift comes from international networks of multilingual scholars of Chinese. They have collaborated to form a critical mass of explicitly comparative, empirical research. Chinese interdisciplinary research has been especially influential in typology, child language, cross-cultural communications, translation and artificial intelligence. Fifty years ago, mainstream conferences, textbooks, books, and journals almost never featured Chinese. Now they routinely do.

The study puts an emphasis on exploring cognitive manipulations contained in the Internet resources (social networks and blogs) that have the greatest impact on students. The study was conducted with 159 students of Don State Technical University. 50 samples of media texts (of various formats) containing cognitive manipulation were taken from social networks sites and blogs. Focus group method, questionnaire, method of Critical Discourse Analysis and methods of mathematical statistics (Principal Component Analysis) were used for data collection and processing. The findings allow us to identify and describe the features of such cognitive manipulation as “presence effect”, “focus on pros”, “halo effect”, “emotional resonance”, “ambiguous language”, “anonymous authority”, “primacy effect”, “exaggeration” and identify the manipulations that have the greatest impact on students. Recommendations aimed at reduction of the impact of manipulative techniques were suggested. The results of the present study may help teachers and psychologists in their work.

The nonconsensual taking or sharing of nude or sexual images, also known as “image-based sexual abuse,” is a major social and legal problem in the digital age. In this chapter, we examine the problem of image-based sexual abuse in the context of digital platform governance. Specifically, we focus on two key governance issues: first, the governance of platforms, including the regulatory frameworks that apply to technology companies; and second, the governance by platforms, focusing on their policies, tools, and practices for responding to image-based sexual abuse. After analyzing the policies and practices of a range of digital platforms, we identify four overarching shortcomings: (1) inconsistent, reductionist, and ambiguous language; (2) a stark gap between the policy and practice of content regulation, including transparency deficits; (3) imperfect technology for detecting abuse; and (4) the responsibilization of users to report and prevent abuse. Drawing on a model of corporate social responsibility (CSR), we argue that until platforms better address these problems, they risk failing victim-survivors of image-based sexual abuse and are implicated in the perpetration of such abuse. We conclude by calling for reasonable and proportionate state-based regulation that can help to better align governance by platforms with CSR-initiatives.

Traditional information retrieval systems return a ranked list of results to a user’s query. This list is often long, and the user cannot explore all the results retrieved. It is also ineffective for a highly ambiguous language such as Arabic. The modern writing style of Arabic excludes the diacritical marking, without which Arabic words become ambiguous. For a search query, the user has to skim over the document to infer if the word has the same meaning they are after, which is a time-consuming task. It is hoped that clustering the retrieved documents will collate documents into clear and meaningful groups. In this paper, we use an enhanced k-means clustering algorithm, which yields a faster clustering time than the regular k-means. The algorithm uses the distance calculated from previous iterations to minimize the number of distance calculations. We propose a system to cluster Arabic search results using the enhanced k-means algorithm, labeling each cluster with the most frequent word in the cluster. This system will help Arabic web users identify each cluster’s topic and go directly to the required cluster. Experimentally, the enhanced k-means algorithm reduced the execution time by 60% for the stemmed dataset and 47% for the non-stemmed dataset when compared to the regular k-means, while slightly improving the purity.

In this perspective piece, the language used in psychiatric classification is considered from a linguistic and anthropological perspective. It is important for psychiatrists to consider how ambiguous language can impact on their view of clinical presentations and the delivery of treatments. Ultimately, delivering care using an empathic and humane approach should always be a primary consideration when treating mental illness.

When building a new programming language, it can be useful to compose parts of existing languages to avoid repeating implementation work. However, this is problematic already at the syntax level, as composing the grammars of language fragments can easily lead to an ambiguous grammar. State-of-the-art parser tools cannot handle ambiguity truly well: either the grammar cannot be handled at all, or the tools give little help to an end-user who writes an ambiguous program. This composability problem is twofold: (i) how can we detect if the composed grammar is ambiguous, and (ii) if it is ambiguous, how can we help a user resolve an ambiguous program? In this paper, we depart from the traditional view of unambiguous grammar design and enable a language designer to work with an ambiguous grammar, while giving users the tools needed to handle these ambiguities. We introduce the concept of resolvable ambiguity wherein a user can resolve an ambiguous program by editing it, as well as an approach to computing the resolutions of an ambiguous program. Furthermore, we present a method based on property-based testing to identify if a composed grammar is unambiguous, resolvably ambiguous, or unresolvably ambiguous. The method is implemented in Haskell and evaluated on a large set of language fragments selected from different languages. The evaluation shows that (i) the approach can handle significantly more cases of language compositions compared to approaches which ban ambiguity altogether, and (ii) that the approach is fast enough to be used in practice. Part of proceedings: ISBN 9781450383257, QC 20230117

Background Reference frames ground spatial communication by mapping ambiguous language (for example, navigation: “to the left”) to properties of the speaker (using a Relative reference frame: “to my left”) or the world (Absolute reference frame: “to the north”). People’s preferences for reference frame vary depending on factors like their culture, the specific task in which they are engaged, and differences among individuals. Although most people are proficient with both reference frames, it is unknown whether preference for reference frames is stable within people or varies based on the specific spatial domain. These alternatives are difficult to adjudicate because navigation is one of few spatial domains that can be naturally solved using multiple reference frames. That is, while spatial navigation directions can be specified using Absolute or Relative reference frames (“go north” vs “go left”), other spatial domains predominantly use Relative reference frames. Here, we used two domains to test the stability of reference frame preference: one based on navigating a four-way intersection; and the other based on the sport of ultimate frisbee. We recruited 58 ultimate frisbee players to complete an online experiment. We measured reaction time and accuracy while participants solved spatial problems in each domain using verbal prompts containing either Relative or Absolute reference frames. Details of the task in both domains were kept as similar as possible while remaining ecologically plausible so that reference frame preference could emerge. Results We pre-registered a prediction that participants would be faster using their preferred reference frame type and that this advantage would correlate across domains; we did not find such a correlation. Instead, the data reveal that people use distinct reference frames in each domain. Conclusion This experiment reveals that spatial reference frame types are not stable and may be differentially suited to specific domains. This finding has broad implications for communicating spatial information by offering an important consideration for how spatial reference frames are used in communication: task constraints may affect reference frame choice as much as individual factors or culture.

Standard economic models cannot capture the fact that information is often ambiguous, and is interpreted in multiple ways. Using a framework that distinguishes between the language in which statements are made and the interpretation of statements, we demonstrate that, unlike in the case where there is no ambiguity, players may come to have different beliefs starting from a common prior, even if they have received exactly the same information, unless the information is common knowledge.

A distance between two languages is a useful tool to measure the language similarity, and is closely related to the intersection problem as well as the shortest string problem. A parsing expression grammar (PEG) is an unambiguous grammar such that the choice operator selects the first matching in PEG while it can be ambiguous in a context-free grammar. PEGs are also closely related to top-down parsing languages. We consider two problems on parsing expression languages (PELs). One is the r-shortest string problem that decides whether or not a given PEL contains a string of length shorter than r. The other problem is the edit-distance problem of PELs with respect to other language families such as finite languages or regular languages. We show that the r-shortest string problem and the edit-distance problem with respect to finite languages are NEXPTIME-complete, and the edit-distance problem with respect to regular languages is undecidable. In addition, we prove that it is impossible to compute a length bound \(\mathcal {B}(G)\) of a PEG G such that L(G) has a string w of length at most \(\mathcal {B}(G)\).

This chapter introduces the role that statistical analysis can play in helping researchers to find and build meaning from quantitative data they have gathered. It provides pathways to information for making judgments and decisions concerning what data might be conveying and what kinds of conclusions might be defensible to draw with respect to research questions and hypotheses. Throughout this book you will be exposed to various concepts specific to the field of statistics. When you read the published research of other researchers or other types of statistics texts, you will invariably encounter one or more of these concepts. It is well-known that unclear, confusing or ambiguous language can interfere with learning, making it much harder than it needs to be. My goal is to help negate such interference. We know that such language can provide a barrier to learning, so the goal here is to demystify that language in preparation for the journey ahead. Accordingly, this chapter also provides an annotated glossary focusing on the language of statistics. For some concepts, other important related concepts in the section are identified for easy cross-referencing purposes.

In this letter, we propose the Interactive Text2Pickup (IT2P) network for human-robot collaboration that enables an effective interaction with a human user despite the ambiguity in user's commands. We focus on the task where a robot is expected to pick up an object instructed by a human, and to interact with the human when the given instruction is vague. The proposed network understands the command from the human user and estimates the position of the desired object first. To handle the inherent ambiguity in human language commands, a suitable question which can resolve the ambiguity is generated. The user's answer to the question is combined with the initial command and given back to the network, resulting in more accurate estimation. The experiment results show that given unambiguous commands, the proposed method can estimate the position of the requested object with an accuracy of 98.49% based on the test dataset. Given ambiguous language commands, we show that the accuracy of the pick up task increases by 1.94 times after incorporating the information obtained from the interaction.

Grammars with contexts are an extension of context-free grammars equipped with operators for referring to the left and the right contexts of a substring being defined. These grammars are notable for still having a cubic-time parsing algorithm, as well as for being able to describe some useful syntactic constructs, such as declaration before use. It is proved in this paper that every language described by a grammar with contexts can be recognized in deterministic linear space.

This paper proposes a model of ambiguous language. We consider a simple cheap talk game in which a sender who faces an ambiguity averse receiver is able to perform ambiguous randomization, i.e. to randomize according to unknown probabilities. We show that for any standard influential communication equilibrium there exists an equilibrium featuring an ambiguous communication strategy which Pareto-dominates it in terms of consistent planning ex ante utilities. Ambiguity, by triggering worst-case decision-making by the receiver, shifts the latter's response to information towards the sender's ideal action, thus encouraging more information transmission.

It is demonstrated that unambiguous conjunctive grammars over a unary alphabet Σ = { a } have non-trivial expressive power, and that their basic properties are undecidable. The key result is that for every base of positional notation, k ⩾ 11 , and for every one-way real-time cellular automaton operating over the alphabet of base-k digits between ⌊ k + 9 4 ⌋ and ⌊ k + 1 2 ⌋ , the language of all strings a n with the base-k representation of the form 1 w 1 , where w is accepted by the automaton, is described by an unambiguous conjunctive grammar. Another encoding is used to simulate a cellular automaton in a unary language containing almost all strings. These constructions are used to show that for every fixed unambiguous conjunctive language L 0 , testing whether a given unambiguous conjunctive grammar generates L 0 is undecidable.

Query modification based on the pseudo relevance feedback(PRF) is an effective way for improving the performance of retrieval system. It is promising approach that used to solve the problems of ambiguous language and synonyms depending on the feedback. In this paper each of expansion and reduction approaches are used for query modification. A hybrid of distribution and association methods are used to select significant terms and expand the query. In this paper, Kullback-Leibler Divergence (KLD) and CHI squared were used as distribution methods that depend on the terms distribution at the top relevant documents and distribute them in the entire corpus. In addition, proximity term frequency method was used to show the semantic relationship between each candidate term with query terms. Different sets of candidate terms are produced from these methods will be combined by Borda aggregation method to get the strength of each individual method. The second direction is removing insignificant terms from the original query and terms' pool to prevent them from being used for expansion query.

Can a machine retrieve the cultural meaning from a corpus of sources? This article addresses the scope and restrictions that digitization, transcription, and data modeling represents for machine-mediated readings of legal, historical records, particularly those derived from the cultural context of Hispanic empire. It compares the dichotomy between the ambiguous language of ancient regime legal texts and the unambiguity required by machinereadable files. Besides, is problematize the corporal reading and the strategy of distant-reading and visualizations as a model for interpretation of vast bulk of textual data. We propose a strategy for segmentation and data modelling for the approach the textual logic of ancient regime legal records based on their hierarchization, interrelation with nonjudiciary sources (theological, historical, philosophical, etc.), its internal segmentation, the non-linear logic of the normative, and the authoritative requirements of compilations and relevant legal works. Its conclude that the advantages of automation are attached to the ability to manipulate files without distorting the original meaning of the texts, therefore, it proposes the necessity to develop standardized vocabularies that help to avoid anachronistic approaches regarding Modern Age legal sources. ¿Puede una máquina recuperar el significado cultural de un corpus de fuentes? Este artículo aborda el alcance y las restricciones que representan la digitalización, la transcripción y el modelado de datos para las lecturas automatizadas de registros legales e históricos, en particular aquellos derivados del contexto cultural del imperio hispano. Compara la dicotomía entre la ambigüedad característica de los textos legales del antiguo régimen y la precisión requerida para la legibilidad automatizada. Además, problematiza la lectura corporal, la estrategia de lectura distante y las visualizaciones como un modelo para la interpretación de la gran mayoría de los datos textuales. Se propone un modelo de segmentación y modelado de datos que aborde la lógica textual de los registros legales del antiguo régimen con base en su jerarquización, interrelación con fuentes no judiciales (teológicas, históricas, filosóficas, entre otras), su segmentación interna, la lógica de lectura no lineal de la normativa, así como los argumentos de autoridad requeridos en compilaciones y trabajos legales relevantes. Concluye que las ventajas de la automatización están asociadas a la capacidad de manipular archivos sin distorsionar el significado original de los textos, por lo tanto, propone la necesidad de desarrollar vocabularios estandarizados que ayuden a evitar enfoques anacrónicos con respecto a las fuentes legales de la Edad Moderna.

Grammars might be used for various other aspects, than just to represent a language. Grammar inference is a large field which main goal is the construction of grammars from various sources. Written text might be analysed indirectly with the use of such inferred grammars. Grammars acquired from processed text might grow into large structures as the inference process could be continuous. We present a method to decompose and store grammars into a non-redundant set of lambda calculus supercombinators. Grammars decomposition is based on their structure and each distinct element is stored only once in such a structure. We present a method that can create such a set from any context-free grammar. To prove this and to show the possible applications in the field of natural language processing we present a case study performed on samples from two books. Those samples are the entire Book of Genesis from The King James Bible and the first 24 chapters of War and peace by Tolstoy. We obtain context-free grammars with the Sequitur algorithm and then we process them with our method. The results show significant decline in the number of grammar elements in all cases.

While there is a growing body of work proposing grammars for music, there is little work testing analytical grammars in a generative setting. We explore the process of learning production probabili...

Website privacy policies often contain ambiguous language that undermines the purpose and value of privacy notices for site users. This paper compares the impact of different regulatory models on the ambiguity of privacy policies in multiple online sectors. First, the paper develops a theory of vague and ambiguous terms. Next, the paper develops a scoring method to compare the relative vagueness of different privacy policies. Then the theory and scoring are applied using natural language processing to rate a set of policies. The ratings are compared against two benchmarks to show whether government-mandated privacy disclosures result in notices that are less ambiguous than those emerging from the market. The methodology and technical tools can provide companies with mechanisms to improve drafting, enable regulators to easily identify poor privacy policies, and empower regulators to more effectively target enforcement actions.

Context-sensitive languages are usually omitted in undergraduate textbooks on Theory of Computation or studied only from structural point of view in graduate textbooks with very few classical examples and no techniques of design of context-sensitive grammars and their corresponding linear bounded automata. Here we present a case of study showing that such omission and lack of examples and techniques can be fulfilled using standard techniques of formal languages. In particular it is stablished the descriptional and time complexity of an ambiguous context-sensitive grammar and a deterministic linear bounded automaton for the context-sensitive language L = { a^mb^nc^mn : m, n >= 1}

Probabilistic grammars define joint probability distributions over sentences and their grammatical structures. They have been used in many areas, such as natural language processing, bioinformatics and pattern recognition, mainly for the purpose of deriving grammatical structures from data (sentences). Unsupervised approaches to learning probabilistic grammars induce a grammar from unannotated sentences, which eliminates the need for manual annotation of grammatical structures that can be laborious and error-prone. In this thesis we study unsupervised learning of probabilistic context-free grammars and probabilistic dependency grammars, both of which are expressive enough for many real-world languages but remain tractable in inference. We investigate three different approaches. The first approach is a structure search approach for learning probabilistic context-free grammars. It acquires rules of an unknown probabilistic context-free grammar through iterative coherent biclustering of the bigrams in the training corpus. A greedy procedure is used in our approach to add rules from biclusters such that each set of rules being added into the grammar results in the largest increase in the posterior of the grammar given the training corpus. Our experiments on several benchmark datasets show that this approach is competitive with existing methods for unsupervised learning of context-free grammars. The second approach is a parameter learning approach for learning natural language grammars based on the idea of unambiguity regularization . We make the observation that natural language is remarkably unambiguous in the sense that each natural language sentence has a large number of possible parses but only a few of the parses are syntactically valid. We incorporate this prior information into parameter learning by means of posterior regularization. The resulting algorithm family contains classic EM and Viterbi EM, as well as a novel softmax-EM algorithm that can be implemented with a simple and efficient extension to classic EM. Our experiments show that unambiguity regularization improves natural language grammar learning, and when combined with other techniques our approach achieves the state-of-the-art grammar learning results. The third approach is grammar learning with a curriculum. A curriculum is a means of presenting training samples in a meaningful order. We introduce the incremental construction hypothesis that explains the benefits of a curriculum in learning grammars and offers some useful insights into the design of curricula as well as learning algorithms. We present results of experiments with (a) carefully crafted synthetic data that provide support for our hypothesis and (b) natural language corpus that demonstrate the utility of curricula in unsupervised learning of real-world probabilistic grammars.

This paper focuses on a multimodal language understanding method for carry-and-place tasks with domestic service robots. We address the case of ambiguous instructions, that is, when the target area is not specified. For instance "put away the milk and cereal" is a natural instruction where there is ambiguity regarding the target area, considering environments in daily life. Conventionally, this instruction can be disambiguated from a dialogue system, but at the cost of time and cumbersome interaction. Instead, we propose a multimodal approach, in which the instructions are disambiguated using the robot's state and environment context. We develop the Multi-Modal Classifier Generative Adversarial Network (MMC-GAN) to predict the likelihood of different target areas considering the robot's physical limitation and the target clutter. Our approach, MMC-GAN, significantly improves accuracy compared with baseline methods that use instructions only or simple deep neural networks., 9 pages, 7 figures, accepted for IEEE Robotics and Automation Letters (RA-L)

We introduce an approach to include formalized mathematics in regular undergraduate mathematics courses. In order to enable automatic parsing and checking, the Open image in new window code of our lecture notes systematically uses strict syntax conventions for all definitions and theorems, including in particular an unambiguous grammar for all formulas. Resulting from several years of experience, we present a body of about 1000 pages of notes for a course on modelling and a sequence of three courses on analysis and calculus which are a regular part in the undergraduate mathematics curriculum at the University of Constance. We explain the basic structure of the formalization and its syntax and discuss the practicability of the approach.

This chapter addresses the question of context in the jurisprudence or case law of the Ad Hoc Tribunals in order to appreciate the position of the contextual elements of the crime from the practical assessment of the definition of the crime. The chapter begins by illustrating the courts’ clear assertion that contextual elements have no place in the literal definition of genocide, and demonstrates the unambiguous acceptance of this position by the courts. However, further analysis demonstrates that despite the lack of reference to contextual elements in the literal definition of the crime, the courts found it irresistible to circumvent the contextual elements in their reasoning without any consistent application of interpretative methods, or any robust demonstration of their choice of arguments or the rules discovery method. Furthermore, the chapter examines how the courts used ambiguous language and tweaked the law in light of the evidentiary challenge presented by the need to prove genocidal intent, and how the courts could have approached the matter without encroaching on the legal ingredients of the crime. The courts supported the characterization of genocide by the individualized intent requirement, yet on the other hand came very close to inclusion of the systematic criminality element, thereby edging dangerously close to the legislators’ sphere. Before the conclusion, the chapter looks at how internationalized and national courts have dealt with the same issue of context to further strengthen its findings.

Organizations often face the challenge of institutional complexity, which involves incompatible prescriptions from multiple institutional logics. To deal with this challenge, prior researchers have proposed several strategies to tackle conflicts within and between organizations. The success of these solutions fundamentally hinges on achieving clarity. However, while clarity often brings further conflicts for both internal and external stakeholders, I argue that ambiguity logic is an alternative approach to deal with institutional complexity as it creates space for negotiations and potential solutions. As such, this paper proposes five research propositions that examine when ambiguous language and behavior can be better used to deal with institutional complexity. In general, the use of ambiguity logic is associated with power. Specifically, ambiguity logic is better applied in organizations when power is more evenly distributed among the stakeholders.

English courts have held that clear words of incorporation of the arbitration clause (contained in the charterparty) are indispensable in the bill of lading, to bind consignees who had never witnessed the charterparty. This approach is for the protection of consignees as third parties. In this article, attention will be paid to the identification of problems relating to the form that a charterparty should have to be appropriate for incorporation. Whether charterparties can be superseded by other types of documents will also be examined. Last but not least, the author will critically assess the rules of construction followed in recent cases where ambiguous language has been used in incorporation clauses in bills of lading. In the last few months, three judgments have been issued which have produced highly controversial outcomes. The author asserts that the method of construction should not be considered as a distinct method from that of incorporation of clauses. Times have changed and, apparently, so has business common sense. However, ‘uncertain certainty’ has been caused because business common sense has been applied differently to judgments that have been issued with a couple of months difference.

Tree adjoining grammars (TAGs) are mildly context sensitive formalisms used mainly in modelling natural languages. Usage and research on these psycho linguistic formalisms have been erratic in the past decade, due to its demanding construction and difficulty to parse. However, they represent promising future for formalism based NLP in multilingual scenarios. In this paper we demonstrate basic synchronous Tree adjoining grammar for English-Tamil language pair that can be used readily for machine translation. We have also developed a multithreaded chart parser that gives ambiguous deep structures and a par dependency structure known as TAG derivation. Furthermore we then focus on a model for training this TAG for each language using a large corpus of text through a map reduce frequency count model in spark and estimation of various probabilistic parameters for the grammar trees thereafter; these parameters can be used to perform statistical parsing on the trained grammar.

Writing a parser remains remarkably painful. Automatic parser generators offer a powerful and systematic way to parse complex grammars, but debugging conflicts in grammars can be time-consuming even for experienced language designers. Better tools for diagnosing parsing conflicts will alleviate this difficulty. This paper proposes a practical algorithm that generates compact, helpful counterexamples for LALR grammars. For each parsing conflict in a grammar, a counterexample demonstrating the conflict is constructed. When the grammar in question is ambiguous, the algorithm usually generates a compact counterexample illustrating the ambiguity. This algorithm has been implemented as an extension to the CUP parser generator. The results from applying this implementation to a diverse collection of faulty grammars show that the algorithm is practical, effective, and suitable for inclusion in other LALR parser generators.

The reduction of ambiguous language is a commonly proposed strategy to remedy non-compliance with international obligations. The European Union conventional arms export control regime is a case in point; here, eliminating ambiguity has stood at the forefront among the strategies that have been proposed to remedy poor implementation. The point of departure of this article, however, is the observation that language-addressing strategies are largely inattentive to the underlying dynamics that caused ambiguity in the first place. Through tracing the formation and evolution of the regime, the article argues that the ambiguity of the export control regime is attributable to a configuration of underlying heterogeneity and resistance that is not conducive to a more precise language. Furthermore, the article argues that in order to explain the adoption, evolution and ambiguity of the regime, we need a theoretical model that moves away from the strong emphasis on norm dynamics prevalent in recent research on arms export control. While norm dynamics and a preference for export restraint have certainly influenced the adoption, evolution and design of the regime, the article highlights how the material interests of export promotion, security and sovereignty feature as more critical variables. This casts new light on the gap between export control commitments and export practice, and provides important clues about the prospects for efficient multilateral arms export control. Pushing the research agenda forward therefore hinges on bringing material interests back into the equation.

Item does not contain fulltext AIMS AND OBJECTIVES: To research the use of ambiguous language in written information concerning patients' functioning and to identify problems resulting from the use of ambiguous language in clinical practice. BACKGROUND: Many projects that aimed to introduce standard terminology concerning patients' functioning in clinical practice are unsuccessful because standard terminology is rarely used in clinical practice. These projects mainly aim to improve communication by reducing ambiguous language. Considering their lack of success, the validity of the argument that language ambiguity is used in clinical practice is questioned. DESIGN: An integrative literature review. METHODS: A systematic search of the MEDLINE (1950-2012) and CINAHL (1982-2012) databases was undertaken, including empirical and theoretical literature. The selected studies were critically appraised using a data assessment and extraction form. RESULTS: Seventeen of 767 papers were included in the review and synthesis. The use of ambiguous language in written information concerning patients' functioning was demonstrated. Problems resulting from the use of ambiguous language in clinical practice were not identified. However, several potential problems were suggested, including hindered clinical decision-making and limited research opportunities. CONCLUSION: The results of this review demonstrated the use of ambiguous language concerning patients' functioning, but health professionals in clinical practice did not experience this issue as a problem. This finding might explain why many projects aimed at introducing standard terminology concerning functioning in clinical practice to solve problems caused by ambiguous language are often unsuccessful. Language ambiguity alone is not a valid argument to justify the introduction of standard terminology. RELEVANCE TO CLINICAL PRACTICE: The introduction of standard terminology concerning patients' functioning will only be successful when clinical practice requires the aggregation and reuse of data from electronic patient records for different purposes, including multidisciplinary decision-making and research.

Parsing plays an important role in static program analysis: during this step a structural representation of code is created upon which further analysis is performed. Parser generator tools, being provided with syntax specification, automate parser development. Language documentation often acts as such specification. Documentation usually takes form of ambiguous grammar in Extended Backus-Naur Form which most parser generators fail to process. Automatic grammar transformation generally leads to parsing performance decrease. Some approaches support EBNF grammars natively, but they all fail to handle ambiguous grammars. On the other hand, Generalized LL parsing algorithm admits arbitrary context-free grammars and achieves good performance, but cannot handle EBNF grammars. The main contribution of this paper is a modification of GLL algorithm which can process grammars in a form which is closely related to EBNF (Extended Context-Free Grammar). We also show that the modification improves parsing performance as compared to grammar transformation-based approach.

International audience; Type-logical grammars use a foundation of logic and type theory to model natural language. These grammars have been particularly successful giving an account of several well-known phenomena on the syntax-semantics interface, such as quantifier scope and its interaction with other phenomena. This chapter gives a high-level description of a family of theorem provers designed for grammar development in a variety of modern type-logical grammars. We discuss automated theorem proving for type-logical grammars from the perspective of proof nets, a graph-theoretic way to represent (partial) proofs during proof search.

Lawyers and policy makers regularly and intentionally use ambiguous language in laws, regulations, and other legal texts. Although ambiguity has important policy benefits, such as interpretive resilience in an ever-changing world, it frustrates engineers and businesses seeking to build software systems that are demonstratively compliant with legal obligations. In this vision paper, we propose a method for modeling legal texts alongside models of software requirements or design artifacts. Our approach allows engineers to reason about regulatory ambiguity separately from their system under development and then trace interpretive decisions made about the legal text to affected requirements models. When a regulation is updated or case law demands a new interpretation of a regulation, engineers can evaluate the effect of the changes on the current design and respond appropriately. Inspired by User Requirements Notation, our proposed method can be implemented as an extension to Legal-GRL.

The universal generation problem for unification grammars is the problem of determining whether a given grammar derives any terminal string with a given feature structure. It is known that the problem is decidable for LFG and PATR grammars if only acyclic feature structures are taken into consideration. In this brief note, we show that the problem is undecidable for cyclic structures. This holds even for grammars that are off-line parsable.

A Szilard language is a language theoretical tool used to describe the derivation process in a formal grammar or grammar system. We investigate computational resources used by (alternating) Turing machines to accept Szilard languages of Chomsky grammars, regulated grammars and grammar systems. The results are related to the circuit complexity classes NC1 and NC2. The paper is a survey of the most important complexity results in the field, but it also brings several new insights into the parallel complexity of Szilard languages of grammar systems. We focus on parallel communicating grammar systems (PCGSs) with context-free components, and we prove that the class of Szilard languages of centralized (returning or non-returning) PCGSs is included in NC1.

Symbolic execution is being successfully used to automatically test statically compiled code. However, increasingly more systems and applications are written in dynamic interpreted languages like Python. Building a new symbolic execution engine is a monumental effort, and so is keeping it up-to-date as the target language evolves. Furthermore, ambiguous language specifications lead to their implementation in a symbolic execution engine potentially differing from the production interpreter in subtle ways. We address these challenges by flipping the problem and using the interpreter itself as a specification of the language semantics. We present a recipe and tool (called Chef) for turning a vanilla interpreter into a sound and complete symbolic execution engine. Chef symbolically executes the target program by symbolically executing the interpreter's binary while exploiting inferred knowledge about the program's high-level structure. Using Chef, we developed a symbolic execution engine for Python in 5 person-days and one for Lua in 3 person-days. They offer complete and faithful coverage of language features in a way that keeps up with future language versions at near-zero cost. Chef-produced engines are up to 1000 times more performant than if directly executing the interpreter symbolically without Chef.

The paper introduces an extension of context-free grammars equipped with an operator for referring to the left context of the substring being defined. For example, a rule A->[email protected]?B defines a symbol a, as long as it is preceded by a string defined by B. The conjunction operator in this example is taken from conjunctive grammars (Okhotin, 2001), which are an extension of ordinary context-free grammars that maintains most of their practical properties, including many parsing algorithms. This paper gives two equivalent definitions of grammars with left contexts-by logical deduction and by language equations-and establishes their basic properties, including a transformation to a normal form and a cubic-time parsing algorithm, with a square-time version for unambiguous grammars.

This paper is a critical analysis of Biggs's deep and surface approaches to learning model, which is prominent in the higher education and tertiary learning fields. The paper reflects on the model's origins and the contextual pressures of the educational landscape extant at that time. It is argued that these pressures have led to a demonstrable lack of serious critique of the model, which has truncated the model's development, leaving it underdeveloped. There are significant problems with the model in the areas of supporting evidence, imprecise conceptualisation, ambiguous language, circularity, and a lack of definition of the underlying structure of deep and surface approaches to learning.

A mathematical apparatus for describing the context-free grammars of artificial languages is presented: the syntax of the language to describe them is defined, as well as logical and generative semantics, and examples are provided to show how the suggested apparatus can be used.

This paper introduces ATTORNEY 209: A Virtual Assistant Adviser for Family-Based Cases. It is a conversational chatbot which is designed to handle initial assessment for families who need legal guidance regarding family cases such as child custody and legal separation. Chart Parsing Algorithm, known in Natural Language Processing, is the approach implemented in this study. It is suitable for ambiguous grammar and uses the dynamic programming approach—partial hypothesized results are stored in a structure called a chart and can be re-used. This eliminates backtracking and prevents a combinatorial

Contextual grammars are introduced by Solomon Marcus in 1969 based on the fundamental concept of descriptive linguistics of insertion of strings in given contexts. Internal contextual grammars are introduced by Paun and Nguyen in 1980. For contextual grammars several descriptional complexity measures and levels of ambiguity have been defined. In this paper, we analyze the trade-off between ambiguity and complexity of languages generated by internal contextual grammars. The notion of a pseudo inherently ambiguous language with respect to two complexity measures is introduced and investigated. These languages can be generated by unambiguous grammars which are minimal with respect to one measure and ambiguous if they are minimal with respect to the other measure. An open problem from [15] is solved in this framework.