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Aspectual Classifications: Use of Raters’ Associations and Co-occurrences of Verbs for Aspectual Classification in German

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Agents and Artificial Intelligence (ICAART 2018)

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Abstract

The present study examines the results of experiments on the automatic classification of German verbs into five aspectual classes [1]: An experiment within an unsupervised framework based on associations of raters [1] and a couple of experiments within a distributional framework, i.e. in window-based and in a subcategorization-frame-based approach [2]. We compare the predictive power of raters’ associations against two types of verbal cooccurrences: i. pure, unstructured co-occurrences and ii. linguistically motivated, well defined co-occurrences which we denote as informed distributional framework. We observed substantial (unsupervised) and excellent (supervised) agreements with a Gold Standard classification.

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Notes

  1. 1.

    [16] refers to these semantic roles as volitional undergoers.

  2. 2.

    As an example of aspectual coercion, consider an atelic verb such as walk, which can be combined with a PP denoting a destination as in he walks to the store and expressing a telic event. The sentence walks to the store is no longer an activity, instead, it is an accomplishment. Aspectual coercion can also be triggered by quantification [18]. A prototypical accomplishment verb such as kill can occur in a sentence expressing an activity, as in he is killing carpet moths (note the present progressive form of the verb) which stands classical tests of activities, e.g. he is killing carpet moths for an hour, permanently/forever. The direct object is a bare plural, expressing cumulative objects [19] which combine well with atelic verbs. With a quantized direct object [18] however, the sentence is clearly telic: he kills two carpet moths in one hour/*for hours.

  3. 3.

    The Vendlerian quadripartition has been modified and extended: [27] added degree achievements, [44] added semelfactices, [45] in contrast defined a tripartition consisting of states, processes and events.

  4. 4.

    Consider the achievement verb find. According to [53] the event of finding has a resultant state, the finding itself however is an atomic event, ignoring a possible complex event structure consisting for instance of discovering something on the ground, taking a decision to pick it up, bending down etc.

  5. 5.

    Tesla (Text Engineering Software LAboratory), see http://tesla.spinfo.uni-koeln.de is an open source virtual research environment, integrating both a visual editor for conducting text-engineering experiments and a Java IDE for developing software components [58].

  6. 6.

    We decided for the heuristics because of economy considerations (Ockham’s razor), giving preference to the simpler method that performs on a par with more complex ones: As [59] show in their paper, performance in tasks like synonym detection is comparable to more sophisticated methods of feature selection, such as taking the most variant elements (see [60]), the most ‘reliable’ (see [61], or to perform a dimensionality reduction (e.g. by singular value decomposition as done in the LSA model, see [6]).

  7. 7.

    The open source framework ELKI (Environment for DeveLoping KDD-Applications Supported by Index-Structures) was developed at the LMU Munich, see http://elki.dbs.ifi.lmu.de.

  8. 8.

    See: https://code.google.com/p/mate-tools/.

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Authors and Affiliations

  1. Department of Automatic Language Processing, Leipzig University, Augustusplatz 10, Leipzig, Germany

    Michael Richter

  2. Institute for Digital Humanities, Cologne University, Albertus-Magnus-Platz, Cologne, Germany

    Jürgen Hermes & Claes Neuefeind

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  1. Michael Richter
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  1. Leiden University, Leiden, The Netherlands

    Jaap van den Herik

  2. University of Porto, Porto, Portugal

    Ana Paula Rocha

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Richter, M., Hermes, J., Neuefeind, C. (2019). Aspectual Classifications: Use of Raters’ Associations and Co-occurrences of Verbs for Aspectual Classification in German. In: van den Herik, J., Rocha, A. (eds) Agents and Artificial Intelligence. ICAART 2018. Lecture Notes in Computer Science(), vol 11352. Springer, Cham. https://doi.org/10.1007/978-3-030-05453-3_22

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