30 research outputs found

    The Curious Case of Metonymic Verbs: A Distributional Characterization

    Get PDF
    Logical metonymy combines an event-selecting verb with an entity-denoting noun (e.g.,The writer began the novel), triggering a covert event interpretation (e.g., reading, writing). Experimental investigations of logical metonymy must assume a binary distinction between metonymic (i.e. event-selecting) verbs and non-metonymic verbs to establish a control condition. However, this binary distinction (whether a verb is metonymic or not) is mostly made on intuitive grounds, which introduces a potential confounding factor. We describe a corpus-based approach which characterizes verbs in terms of their behavior at the syntax-semantics interface. The model assesses the extent to which transitive verbs prefer event-denoting objects over entity-denoting objects. We then test this “eventhood” measure on psycholinguistic datasets, showing that it can distinguish not only metonymic from non-metonymic verbs, but that it can also capture more fine-grained distinctions among different classes of metonymic verbs, putting such distinctions into a new graded perspective

    Fitting, Not Clashing! A Distributional Semantic Model of Logical Metonymy

    Get PDF
    Logical metonymy interpretation (e.g. begin the book ->writing) has received wide attention in linguistics. Experimental results have shown higher processing costs for metonymic conditions compared with non-metonymic ones ( read the book). According to a widely held interpretation, it is the type clash between the event-selecting verb and the entity-denoting object (begin the book) that triggers coercion mechanisms and leads to additional processing effort. We propose an alternative explanation and argue that the extra processing effort is an effect of thematic fit. This is a more economical hypothesis that does not need to postulate a separate type clash mechanism: entity-denoting objects simply have a low fit as objects of event-selecting verbs. We test linguistic datasets from psycholinguistic experiments and find that a structured distributional model of thematic fit, which does not encode any explicit argument type information, is able to replicate all significant experimental findings. This result provides evidence for a graded account of coercion phenomena in which thematic fit accounts for both the trigger of the coercion and the retrieval of the covert even

    Inferring Covert Events in Logical Metonymies: a Probe Recognition Experiment

    No full text
    It has been widely acknowledged that the interpretation of log- ical metonymies involves the interpretation of covert events (begin the book → reading / writing). Whether this implicit content is part of our lexicon or rather derives from general pragmatic inference, it is currently subject of debate. We present results from a probe recognition experiment, providing novel evidence in support of early metonymy processing, consistent with the hypothesis that covert events are retrieved from knowledge of typical events activated by lexical items

    EvalIta 2011: The Frame Labeling over Italian Texts Task

    No full text

    Design and Realization of a Modular Architecture for Textual Entailment

    No full text
    A key challenge at the core of many Natural Language Processing (NLP) tasks is the ability to determine which conclusions can be inferred from a given natural language text. This problem, called the Recognition of Textual Entailment (RTE), has initiated the development of a range of algorithms, methods, and technologies. Unfortunately, research on Textual Entailment (TE), like semantics research more generally, is fragmented into studies focussing on various aspects of semantics such as world knowledge, lexical and syntactic relations, or more specialized kinds of inference. This fragmentation has problematic practical consequences. Notably, interoperability among the existing RTE systems is poor, and reuse of resources and algorithms is mostly infeasible. This also makes systematic evaluations very difficult to carry out. Finally, textual entailment presents a wide array of approaches to potential end users with little guidance on which to pick. Our contribution to this situation is the novel EXCITEMENT architecture, which was developed to enable and encourage the consolidation of methods and resources in the textual entailment area. It decomposes RTE into components with strongly typed interfaces. We specify (a) a modular linguistic analysis pipeline and (b) a decomposition of the ‘core’ RTE methods into top-level algorithms and subcomponents. We identify four major subcomponent types, including knowledge bases and alignment methods. The architecture was developed with a focus on generality, supporting all major approaches to RTE and encouraging language independence. We illustrate the feasibility of the architecture by constructing mappings of major existing systems onto the architecture. The practical implementation of this architecture forms the EXCITEMENT open platform. It is a suite of textual entailment algorithms and components which contains the three systems named above, including linguistic-analysis pipelines for three languages (English, German, and Italian), and comprises a number of linguistic resources. By addressing the problems outlined above, the platform provides a comprehensive and flexible basis for research and experimentation in textual entailment and is available as open source software under the GNU General Public License
    corecore