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Linguistic expressions of confusion, namely confusion markers, construe discrepancies between an academic author's prior knowledge and the information received. These emotive responses motivate knowledge-seeking behaviors to dissolve cognitive incongruities and are inherently connected with knowledge-making. Limited research has, however, examined how they partake in knowledge construction and dissemination in academic writing. Drawing on a frame-based analytical approach, this study investigated how an academic author's disciplinary background and time of publication may mediate the use of confusion markers in 640 research articles sampled from four disciplines. The corpus-based analyses were complemented by insights from 16 specialists to explore how considerations underlying their use of confusion markers shaped their academic writing. The findings indicated that the overall use of confusion markers changed over time and that disciplinary background and time of publication were significant predictors of several frame elements. The observed disciplinary and diachronic patterns of use can be explained in terms of epistemological orientations, developments in the academic world such as increasing disciplinary specialization and growing interdisciplinary research leading to a broadening of readership, and stiff competition in scholarly publication. [ABSTRACT FROM AUTHOR]

The English verbal prefix out- gives rise to at least two semantic categories: comparative forms as in to outplay someone and locative forms as in to outstream from somewhere. While most available studies on the comparative sense rely on insufficient databases, systematic studies on the actual behavior of locative verbal out-forms are lacking altogether. Building on a set of more than 1,500 tokens culled from corpora, this study is the first to systematically analyze, formalize, and contrast the two senses. The formal analysis will be couched in frame semantics and model both individual attested examples as well as lexeme-formation rules based on generalizations. Formalizations of the two prefixes, and their implications, are shown to speak against an analysis of one underlying, underspecified prefix. Locative out- essentially functions as a morphologically bound, and highly restricted, version of out- as a particle, while comparative out- is a highly specialized, idiosynchratic construction. [ABSTRACT FROM AUTHOR]

We present an axiomatization of the non-associative Lambek calculus extended with classical negation for which the frame semantics with the classical interpretation of negation is sound and complete. [ABSTRACT FROM AUTHOR]

Compliance analysis requires legal counsel but is generally unavailable in many software projects. Analysis of legal text using logic-based models can help developers understand requirements for the development and use of software-intensive systems throughout its lifecycle. We outline a practical modeling process for norms in legally binding agreements that include contractual rights and obligations. A computational norm model analyzes available rights and required duties based on the satisfiability of situations, a state of affairs, in a given scenario. Our method enables modular norm model extraction, representation, and reasoning. For norm extraction, using the theory of frame semantics, we construct two foundational norm templates for linguistic guidance. These templates correspond to Hohfeld's concepts of claim-right and its jural correlative, duty. Each template instantiation results in a norm model, encapsulated in a modular unit which we call a super-situation that corresponds to an atomic fragment of law. For hierarchical modularity, super-situations contain a primary norm that participates in relationships with other norm models. Norm compliance values are logically derived from its related situations and propagated to the norm's containing super-situation, which in turn participates in other super-situations. This modularity allows on-demand incremental modeling and reasoning using simpler model primitives than previous approaches. While we demonstrate the usefulness of our norm models through empirical studies with contractual statements in open source software and privacy domains, its grounding in theories of law and linguistics allows wide applicability. [ABSTRACT FROM AUTHOR]

Every Berman's variety K p q which is the subvariety of Ockham algebras defined by the equation ∼ 2 p + q a = ∼ q a ( p ≥ 1 and q ≥ 0 ) determines a finitary substitution invariant consequence relation ⊢ p q . A sequent system S p q is introduced as an axiomatization of the consequence relation ⊢ p q . The system S p q is characterized by a single finite frame F p q under the frame semantics given for the formal language. By the duality between frames and algebras, S p q can be viewed as a 4 2 p + q -valued logic as it is characterized by a distributive lattice of 4 2 p + q elements with a unary operator. Moreover, a structural-rule-free, cut-free and terminating sequent system G p q is established for ⊢ p q . The Craig interpolation property of ⊢ p q is shown proof-theoretically utilizing G p q . [ABSTRACT FROM AUTHOR]

In this paper we present a database management and annotation tool for running an enriched FrameNet database, the FrameNet Brasil WebTool. We demonstrate how the entity-based model of such a tool allows for the addition of two types of data-structure to FrameNet Brasil, both of which aimed at refining the granularity of the semantic representations: the frame element-to-frame and the ternary qualia relations. We report on three proof-of-concept applications of such an enriched database: a domain-specific structured lexicon, a recommendation system for tourists and a post-editing system for domain adaptation in machine translation. [ABSTRACT FROM AUTHOR]

With the increase use of microblogs and social media platforms as forms of on-line communication, we now have a huge amount of opinionated data reflecting people's opinions and attitudes in form of reviews, forum discussions, blogs and tweets. This has recently brought great interest to sentiment analysis and opinion mining field that analyzes people's feelings and attitudes from written language. Most of the existing approaches on sentiment analysis rely mainly on the presence of affect words that explicitly reflect sentiment. However, these approaches are semantically weak, that is, they do not take into account the semantics of words when detecting their sentiment in text. Only recently a few approaches (e.g. sentic computing) started investigating towards this direction. Following this trend, this paper investigates the role of semantics in sentiment analysis of social media. To this end, frame semantics and lexical resources such as BabelNet are employed to extract semantic features from social media that lead to more accurate sentiment analysis models. Experiments are conducted with different types of semantic information by assessing their impact in four social media datasets which incorporate tweets, blogs and movie reviews. A tenfold cross-validation shows that F1 measure increases significantly when using semantics in sentiment analysis in social media. Results show that the proposed approach considering word's semantics for sentiment analysis surpasses non-semantic approaches for the considered datasets. [ABSTRACT FROM AUTHOR]

Text mining techniques have been recently employed to classify and summarize user reviews on mobile application stores. However, due to the inherently diverse and unstructured nature of user-generated online textual data, text-based review mining techniques often produce excessively complicated models that are prone to overfitting. In this paper, we propose a novel approach, based on frame semantics, for app review mining. Semantic frames help to generalize from raw text (individual words) to more abstract scenarios (contexts). This lower-dimensional representation of text is expected to enhance the predictive capabilities of review mining techniques and reduce the chances of overfitting. Specifically, our analysis in this paper is two-fold. First, we investigate the performance of semantic frames in classifying informative user reviews into various categories of actionable software maintenance requests. Second, we propose and evaluate the performance of multiple summarization algorithms in generating concise and representative summaries of informative reviews. Three different datasets of app store reviews, sampled from a broad range of application domains, are used to conduct our experimental analysis. The results show that semantic frames can enable an efficient and accurate review classification process. However, in review summarization tasks, our results show that text-based summarization generates more comprehensive summaries than frame-based summarization. Finally, we introduces MARC 2.0, a review classification and summarization suite that implements the algorithms investigated in our analysis. [ABSTRACT FROM AUTHOR]

This paper describes the design and implementation of a computational model for Arabic natural language semantics, a semantic parser for capturing the deep semantic representation of Arabic text. The parser represents a major part of an Interlingua-based machine translation system for translating Arabic text into Sign Language. The parser follows a frame-based analysis to capture the overall meaning of Arabic text into a formal representation suitable for NLP applications that need for deep semantics representation, such as language generation and machine translation. We will show the representational power of this theory for the semantic analysis of texts in Arabic, a language which differs substantially from English in several ways. We will also show that the integration of WordNet and FrameNet in a single unified knowledge resource can improve disambiguation accuracy. Furthermore, we will propose a rule based algorithm to generate an equivalent Arabic FrameNet, using a lexical resource alignment of FrameNet1.3 LUs and WordNet3.0 synsets for English Language. A pilot study of motion and location verbs was carried out in order to test our system. Our corpus is made up of more than 2000 Arabic sentences in the domain of motion events collected from Algerian first level educational Arabic books and other relevant Arabic corpora. [ABSTRACT FROM AUTHOR]

Semantic role labeling is traditionally viewed as a sentence-level task concerned with identifying semantic arguments that are overtly realized in a fairly local context (i.e., a clause or sentence). However, this local view potentially misses important information that can only be recovered if local argument structures are linked across sentence boundaries. One important link concerns semantic arguments that remain locally unrealized (null instantiations) but can be inferred from the context. In this paper, we report on the SemEval 2010 Task-10 on 'Linking Events and Their Participants in Discourse', that addressed this problem. We discuss the corpus that was created for this task, which contains annotations on multiple levels: predicate argument structure (FrameNet and PropBank), null instantiations, and coreference. We also provide an analysis of the task and its difficulties. [ABSTRACT FROM AUTHOR]

This paper will focus on recent and near-term future developments at FrameNet (FN) and the interoperability issues they raise. We begin by discussing the current state of the Berkeley FN database including major changes in the data format for the latest data release. We then briefly review two recent local projects, "Rapid Vanguarding', which has created a new interface for the frame and lexical unit definition process based on the Word Sketch Engine of Kilgarriff et al. (), and 'Beyond the Core', which has developed tools for annotating constructions, and created a sample 'construction' of especially 'interesting' constructions which are neither simply lexical nor easy for the standard parsers to parse. We also cover two current collaborations, FN's part in the development of the manually annotated subcorpus of the American National Corpus, and a pilot study on aligning WordNet and FrameNet, to exploit the complementary strengths of these quite different resources. We discuss FN-related research on Spanish, Japanese, German (SALSA), Chinese and other languages, and the language-independence of frames, along with interesting FN-related work by others, and a sketch of a large group of image-schematic frames which are now being added to FN. We close with some ideas about how FrameNet can be opened up, to allow broader participation in the development process without losing precision and coherence, including a small-scale study on acquiring data for FN using Amazon's Mechanical Turk crowd-sourcing system. [ABSTRACT FROM AUTHOR]

Corpora with high-quality linguistic annotations are an essential component in many NLP applications and a valuable resource for linguistic research. For obtaining these annotations, a large amount of manual effort is needed, making the creation of these resources time-consuming and costly. One attempt to speed up the annotation process is to use supervised machine-learning systems to automatically assign (possibly erroneous) labels to the data and ask human annotators to correct them where necessary. However, it is not clear to what extent these automatic pre-annotations are successful in reducing human annotation effort, and what impact they have on the quality of the resulting resource. In this article, we present the results of an experiment in which we assess the usefulness of partial semi-automatic annotation for frame labeling. We investigate the impact of automatic pre-annotation of differing quality on annotation time, consistency and accuracy. While we found no conclusive evidence that it can speed up human annotation, we found that automatic pre-annotation does increase its overall quality. [ABSTRACT FROM AUTHOR]

This note explains an error in Restall’s ‘Simplified Semantics for Relevant Logics (and some of their rivals)’ (Restall, J Philos Logic 22(5):481–511, ) concerning the modelling conditions for the axioms of assertion A → (( A → B) → B) (there called c6) and permutation ( A → ( B → C)) → ( B → ( A → C)) (there called c7). We show that the modelling conditions for assertion and permutation proposed in ‘Simplified Semantics’ overgenerate. In fact, they overgenerate so badly that the proposed semantics for the relevant logic R validate the rule of disjunctive syllogism. The semantics provides for no models of R in which the “base point” is inconsistent. This problem is not restricted to ‘Simplified Semantics.’ The techniques of that paper are used in Graham Priest’s textbook An Introduction to Non-Classical Logic (Priest, ), which is in wide circulation: it is important to find a solution. In this article, we explain this result, diagnose the mistake in ‘Simplified Semantics’ and propose two different corrections. [ABSTRACT FROM AUTHOR]

In this paper we propose a semantic apparatus based on Frame Semanticswhich enables us to treat the systematic polysemy of Danish motionverbs in a satisfactory way in relation to Machine Translation (MT).Abandoning the strategy applied in more traditional MT systems whererelated and unrelated meanings are in essence treated alike, i.e. asunrelated, we suggest an approach where relatedness in meaning isexpressed via frame element assignments and where systematicallyderived senses can thus be generated on the basis of prototypicalsenses. By contrasting Danish data with Spanish, we demonstrate thatthe identified meaning variations in Danish motion verbs are crucialnot only for analysis but also in the transfer phase where deviationsin evoked frame elements prove to trigger translations which differfrom the “prototypical” translations of the relevant verbs. [ABSTRACT FROM AUTHOR]