Result filters

Metadata provider

Language

Resource type

Availability

Active filters:

  • Organisation: Institute for the Dutch Language
  • Language: English
26 record(s) found

Search results

  • Blacklab AutoSearch Corpus Search

    This demonstrator allows users to define one or more corpora and upload data for the corpora, after which the corpora will be made automatically searchable in a private workspace. Users can upload text data annotated with lemma + part of speech tags in TEI or FoLiA format, either as a single XML file or as an archive (zip or tar.gz) containing several XML files. Corpus size is limited to begin with (25 MB limit per uploaded file; 500,000 token limit for an entire corpus), but these limits may be increased at a later point in time. The search application is powered by the INL BlackLab corpus search engine. The search interface is the same as the one used in for example the Corpus of Contemporary Dutch / Corpus Hedendaags Nederlands.

  • Corpus of Contemporary Dutch

    The Corpus of Contemporary Dutch (Corpus Hedendaags Nederlands (CLARIN)) is a collection of texts consisting of more than 800,000 texts from newspapers, journals, TV News broadcasts and legal materials (1814-2013). The corpus was created by combining the older 5, 27 and 38 million words corpora and the Parole Corpus, supplemented by newspaper texts from NRC and De Standaard (until 2013). In addition, it contains corpus material from Suriname and the Dutch Antilles.
    Corpus Hedendaags Nederlands (CLARIN) is een tekstverzameling van meer dan 800.000 teksten uit kranten, tijdschriften, journaaluitzendingen en juridisch materiaal (1814-2013). Het corpus is een samenvoeging van het oude 5, 27 en 38 Miljoen Woorden Corpus en het PAROLE Corpus, aangevuld met krantenteksten uit NRC en De Standaard (tot 2013). Daarnaast bevat het corpus materiaal uit Suriname en de Antillen.

  • WebCelex

    WebCelex is a webbased interface to the CELEX lexical databases of English, Dutch and German. CELEX was developed as a joint enterprise of the University of Nijmegen, the Institute for Dutch Lexicology in Leiden, the Max Planck Institute for Psycholinguistics in Nijmegen, and the Institute for Perception Research in Eindhoven. For each language, the database contains detailed information on: orthography (variations in spelling, hyphenation), phonology (phonetic transcriptions, variations in pronunciation, syllable structure, primary stress), morphology (derivational and compositional structure, inflectional paradigms), syntax (word class, word class-specific subcategorizations, argument structures) and word frequency (summed word and lemma counts, based on recent and representative text corpora).

  • Dictionary of Middle Dutch

    Search Application for the Middle Dutch Dictionary, which describes the vocabulary of the Dutch language as spoken from the 13th till the 16th century. .
    Zoekapplicatie voor het Middelnederlandsch Woordenboek, dat de woordenschat beschrijft van het Nederlands dat in de dertiende tot de zestiende eeuw gesproken werd.
    Modern Dutch Lemma
    Describes the origin of a word
    describes the meaning of a words
    describes the structure of a word

  • Dictionary of Old Dutch

    The dictionary of Old Dutch (ONW) online is the electronic version of the ONW. The dictionary describes describes the Old Dutch vocabulary from the period 500 to 1200.
    Modern Dutch Lemma
    Describes the origin of a word
    describes the meaning of a words
    describes the structure of a word

  • Frog: An advanced Natural Language Processing suite for Dutch

    Frog's current version will tokenize, tag, lemmatize, and morphologically segment word tokens in Dutch text files, will assign a dependency graph to each sentence, will identify the base phrase chunks in the sentence, and will attempt to find and label all named entities.
    Van den Bosch, A., Busser, G.J., Daelemans, W., and Canisius, S. (2007). An efficient memory-based morphosyntactic tagger and parser for Dutch, In F. van Eynde, P. Dirix, I. Schuurman, and V. Vandeghinste (Eds.), Selected Papers of the 17th Computational Linguistics in the Netherlands Meeting, Leuven, Belgium, pp. 99-114

  • Namescape Search

    Searching and visualizing Named Entities in modern Dutch novels. The named entity (NE) tagging and resolution in NameScape enables quantitative and repeatable research where previously only guesswork and anecdotal evidence was feasible. The visualisation module enables researchers with a less technical background to draw conclusions about functions of names in literary work and help them to explore the material in search of more interesting questions (and answers). Users from other communities (sociolinguistics, sentiment analysis, …) also benefit from the NE tagged data, especially since the NE recognizer is available as a web service, enabling researchers to annotate their own research data. Datasets in NameScape (total of 1.129 books): Corpus Sanders: A corpus of 582 Dutch novels written and published between 1970 and 2009 will. Corpus Huygens: Consists of 22 novels manually tagged with detailed named entity information. IPR for this corpus do not allow distribution. Corpus eBooks: Consists of 7000+ Dutch eBooks tagged automatically with basic NER features and person name Part information. IPR for this corpus do not allow distribution. Corpus SoNaR Books: 105 Dutch books; NE tagged. Corpus Gutenberg Dutch: Consists of 530 NE tagged TEI files converted from the Epub versions of the corresponding Gutenberg documents. Recent research has conclusively proven names in literary works can only be put fully into perspective when studied in a wider context (landscape) of names either in the same text or in related material (the onymic landscape or “namescape”). Research on large corpora is needed to gain a better understanding of e.g. what is characteristic for a certain period, genre, author or cultural region. The data necessary for research on this scale simply does not exist yet. NameScape aims to fill the need by providing a substantial amount of literary works annotated with a rich tag set, thereby enabling researchers to perform their research in more depth than previously possible. Several exploratory visualization tools help the scholar to answer old questions and uncover many more new ones, which can be addressed using the demonstrator.
    de Does, J, Depuydt, K, van Dalen-Oskam, K and Marx, M. 2017. Namescape: Named Entity Recognition from a Literary Perspective. In: Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 361–370. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.30. License: CC-BY 4.0
    Karina van Dalen-Oskam (2013), Nordic Noir: a background check on Inspector Van Veeteren, 31 May 2012, http://blog.namescape.nl/?p=47