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  1. pyMMAX2: Deep access to MMAX2 projects from Python
    Erschienen: 2022
    Verlag:  Stroudsburg, Pennsylvania : Association for Computational Linguistics ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    pyMMAX2 is an API for processing MMAX2 stand-off annotation data in Python. It provides a lightweight basis for the development of code which opens up the Java- and XML-based ecosystem of MMAX2 for more recent, Python-based NLP and data science... mehr

     

    pyMMAX2 is an API for processing MMAX2 stand-off annotation data in Python. It provides a lightweight basis for the development of code which opens up the Java- and XML-based ecosystem of MMAX2 for more recent, Python-based NLP and data science methods. While pyMMAX2 is pure Python, and most functionality is implemented from scratch, the API re-uses the complex implementation of the essential business logic for MMAX2 annotation schemes by interfacing with the original MMAX2 Java libraries. pyMMAX2 is available for download at github.com/nlpAThits/pyMMAX2.

     

    Export in Literaturverwaltung
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Konferenzveröffentlichung
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Computerlinguistik; Python; API; XML; Neurolinguistisches Programmieren; Data Science
    Lizenz:

    creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/openAccess

  2. Knowledge sources for bridging resolution in multi-party dialog
    Erschienen: 2022
    Verlag:  Paris : European Language Resources Association (ELRA) ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    In this paper we investigate the coverage of the two knowledge sources WordNet and Wikipedia for the task of bridging resolution. We report on an annotation experiment which yielded pairs of bridging anaphors and their antecedents in spoken... mehr

     

    In this paper we investigate the coverage of the two knowledge sources WordNet and Wikipedia for the task of bridging resolution. We report on an annotation experiment which yielded pairs of bridging anaphors and their antecedents in spoken multi-party dialog. Manual inspection of the two knowledge sources showed that, with some interesting exceptions, Wikipedia is superior to WordNet when it comes to the coverage of information necessary to resolve the bridging anaphors in our data set. We further describe a simple procedure for the automatic extraction of the required knowledge from Wikipedia by means of an API, and discuss some of the implications of the procedure’s performance.

     

    Export in Literaturverwaltung
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Konferenzveröffentlichung
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Dialog; WordNet; Wikipedia; Gesprochene Sprache; Information; Datensatz; Wissensextraktion; API; Diskurs; Semantic Web; Lexikon
    Lizenz:

    creativecommons.org/licenses/by-nc-sa/3.0/ ; info:eu-repo/semantics/openAccess

  3. An API for discourse-level access to XML-encoded corpora
    Erschienen: 2022
    Verlag:  Paris : European Language Resources Association (ELRA) ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    We describe a simple and efficient Java object model and application programming interface (API) for (possibly multi-modal) annotated natural language corpora. Corpora are represented as elements like Sentences, Turns, Utterances, Words, Gestures and... mehr

     

    We describe a simple and efficient Java object model and application programming interface (API) for (possibly multi-modal) annotated natural language corpora. Corpora are represented as elements like Sentences, Turns, Utterances, Words, Gestures and Markables. The API allows linguists to access corpora in terms of these discourse-level elements, i.e. at a conceptual level they are familiar with, with the flexibility offered by a general purpose programming language. It is also a contribution to corpus standardization efforts because it is based on a straightforward and easily extensible data model which can serve as a target for conversion of different corpus formats.

     

    Export in Literaturverwaltung
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Konferenzveröffentlichung
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: API; XML; Korpus; Natürliche Sprache; Vereinheitlichung; Datenmodell; Softwarewiederverwendung
    Lizenz:

    creativecommons.org/licenses/by-nc-sa/3.0/ ; info:eu-repo/semantics/openAccess

  4. Lexical data API
    Erschienen: 2022
    Verlag:  Mannheim : IDS-Verlag ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    This API provides data from various dictionary resources of K Dictionaries across 50 languages. It is used by language service providers, app developers, and researchers, and returns data as JSON documents. A basic search result consists of an object... mehr

     

    This API provides data from various dictionary resources of K Dictionaries across 50 languages. It is used by language service providers, app developers, and researchers, and returns data as JSON documents. A basic search result consists of an object containing partial lexical information on entries that match the search criteria, but further in-depth information is also available. Basic search parameters include the source resource, source language, and text (lemma), and the entries are returned as objects within the results array. It is possible to look for words with specific syntactic criteria, specifying the part of speech, grammatical number, gender and subcategorization, monosemous or polysemous entries. When searching by parameters, each entry result contains a unique entry ID, and each sense has its own unique sense ID. Using these IDs, it is possible to obtain more data – such as syntactic and semantic information, multiword expressions, examples of usage, translations, etc. – of a single entry or sense. The software demonstration includes a brief overview of the API with practical examples of its operation.

     

    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Aufsatz aus einem Sammelband
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Wörterbuch; Compterunterstützte Lexikographie; API; Cluster <Datenanalyse>
    Lizenz:

    creativecommons.org/licenses/by-sa/4.0/deed.de ; info:eu-repo/semantics/openAccess