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  • Language: Dutch
  • Organisation: Utrecht University
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  • 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).

  • LASSY Word Relations Search Web Application

    The LASSY word relations web application makes it possible to search for sentences that contain pairs of words between which there is a grammatical relation. One can search in the Dutch LASSY-SMALL Treebank (1 million tokens), in which the syntactic parse of each sentence has been manually verified, and in (a part of) the LASSY-LARGE Treebank (700 million tokens ),in which the syntactic parse of each sentence has been added by the automatic parser Alpino. One can restrict the query to search for words of a particular Part-of-Speech, which is very useful in the case of syntactic ambiguities. One can also leave out the string of the word, so that one can obtain e.g. a list of sentences in which any adverb modifies a given verb, or even any word modifies a given verb. On the page that lists the found sentences one can view the exact syntactic structure of each sentence by a simple click. The application also provides detailed frequency information of all found sentences and word pairs. The Lassy treebanks have been made by the KU Leuven and the Rijksuniversiteit Groningen through financing of the Dutch Language Union. One can obtain these treebanks through the HLT Agency (TST-Centrale). Use PaQu (http://dev.clarin.nl/node/4182) for many more options and if you want to search for word pairs in your own text corpus.

  • PICCL: Philosophical Integrator of Computational and Corpus Libraries

    PICCL is a set of workflows for corpus building through OCR, post-correction, modernization of historic language and Natural Language Processing. It combines Tesseract Optical Character Recognition, TICCL functionality and Frog functionality in a single pipeline. Tesseract offers Open Source software for optical character recognition. TICCL (Text Induced Corpus Clean-up) is a system that is designed to search a corpus for all existing variants of (potentially) all words occurring in the corpus. This corpus can be one text, or several, in one or more directories, located on one or more machines. TICCL creates word frequency lists, listing for each word type how often the word occurs in the corpus. These frequencies of the normalized word forms are the sum of the frequencies of the actual word forms found in the corpus. TICCL is a system that is intended to detect and correct typographical errors (misprints) and OCR errors (optical character recognition) in texts. When books or other texts are scanned from paper by a machine, that then turns these scans, i.e. images, into digital text files, errors occur. For instance, the letter combination `in' can be read as `m', and so the word `regeering' is incorrectly reproduced as `regeermg'. TICCL can be used to detect these errors and to suggest a correct form. Frog enriches textual documents with various linguistic annotations.
    Martin Reynaert, Maarten van Gompel, Ko van der Sloot and Antal van den Bosch. 2015. PICCL: Philosophical Integrator of Computational and Corpus Libraries. Proceedings of CLARIN Annual Conference 2015, pp. 75-79. Wrocław, Poland. http://www.nederlab.nl/cms/wp-content/uploads/2015/10/Reynaert_PICCL-Philosophical-Integrator-of-Computational-and-Corpus-Libraries.pdf
    PICCL

  • Nederlab, online laboratory for humanities research on Dutch text collections

    The Nederlab project aims to bring together all digitized texts relevant to Dutch national heritage, the history of Dutch language and culture (c. 800 - present) in one user-friendly and tool-enriched open access web interface, allowing scholars to simultaneously search and analyze data from texts spanning the full recorded history of the Netherlands, its language and culture. The project builds on various initiatives: for corpora Nederlab collaborates with the scientific libraries and institutions, for infrastructure with CLARIN (and CLARIAH), for tools with eHumanities programmes such as Catch, IMPACT and CLARIN (TICCL, frog). Nederlab will offer a large number of search options with which researchers can find the occurrence of a particular term in a particular corpus or subcorpus. It'll also offer visualization of search results through line graphs, bar graphs, circle graphs, or scatter graphs. Furthermore, this online lab will offer a large set of tools, like tokenization tools, tools for spelling normalization, PoS-tagging tools, lemmatization tools, a computational historical lexicon and indices. Also, the use of (semi-) automatic syntactic parsing, tools for text mining, data mining and sentiment mining, Named Entity Recognition tools, coreference resolution tools, plagiarism detection tools, paraphrase detection tools and cartographical tools is offered The first version of Nederlab was launched in early 2015, it’ll be expanded until the end of 2017. Nederlab is financed by NWO, KNAW, CLARIAH and CLARIN-NL.
    http://www.nederlab.nl/wp/?page_id=12

  • Frog: An advanced Natural Language Processing Suite for Dutch (Web Service and Application)

    Frog is an integration of memory-based natural language processing (NLP) modules developed for Dutch. It performs automatic linguistic enrichment such as part of speech tagging, lemmatisation, named entity recognition, shallow parsing, dependency parsing and morphological analysis. All NLP modules are based on TiMBL.
    Iris Hendrickx, Antal van den Bosch, Maarten van Gompel, Ko van der Sloot and Walter Daelemans. 2016.Frog: A Natural Language Processing Suite for Dutch. CLST Technical Report 16-02, pp 99-114. Nijmegen, the Netherlands. https://github.com/LanguageMachines/frog/blob/master/docs/frogmanual.pdf
    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. http://ilk.uvt.nl/downloads/pub/papers/tadpole-final.pdf
    Frog (plain text input)
    Frog (folia+xml input)

  • Ucto Tokeniser

    Ucto tokenizes text files: it separates words from punctuation, and splits sentences. This is one of the first tasks for almost any Natural Language Processing application. Ucto offers several other basic preprocessing steps such as changing case that you can all use to make your text suited for further processing such as indexing, part-of-speech tagging, or machine translation. The tokeniser engine is language independent. By supplying language-specific tokenisation rules in an external configuration file a tokeniser can be created for a specific language. Ucto comes with tokenization rules for English, Dutch, French, Italian, and Swedish; it is easily extendible to other languages. It recognizes dates, times, units, currencies, abbreviations. It recognizes paired quote spans, sentences, and paragraphs. It produces UTF8 encoding and NFC output normalization, optionally accepts other encodings as input. Optional conversion to all lowercase or uppercase. Ucto supports FoLiA XML.
    Ucto

  • GrNe: Greek-Dutch dictionary

    Online dictionary (ancient) Greek - Dutch for the letter Pi. Search functions include searches for Greek lemmata, search of Greek declined or conjugated word-forms that lead to the correct lemma ('lemmatizer'), searches for Dutch words leading to different Greek lemmata, and etymological searches. The dictionary is linked to Logeion, the international website of Greek dictionaries at the University of Chicago. The developers estimate that a complete version of the dictionary will be finished by the end of 2015 and that it will be published by the end of 2016. A new dictionary ancient Greek – Dutch is currently under construction at Leiden University. The dictionary is being financed through the 2010 Spinoza award of project director Ineke Sluiter. CLARIN funding enabled the digital production of the letter Pi. Currently, the letters beta, gamma, zeta, pi and sigma are available online. The developers estimate that a complete first version of the dictionary will be finished by the end of 2015 and that it will be published by the end of 2016. The corpus that is being covered by this dictionary covers Greek literature from its beginnings (Homer) and consists of ca. 3.680.000 words (tokens); it includes all classical authors from the 5th and 4th centuries BCE, and a selection of later Greek (selection based on the likelihood that the text will be used by our target groups), but all of the New Testament, Lucian and Plutarch. The dictionary will eventually contain ca. 52.500 headwords. It is based on a thorough comparison of state of the art dictionaries, supplemented with the help of the material from the Thesaurus Linguae Graecae. Greek morphology is complicated. In order to use a dictionary effectively, a rather high level of initial language competence is necessary for the user to be able to relate the word-form s/he finds in a text to the correct basic lemma form, where the definition of the word can be found. This digital dictionary however has an added ‘lemmatizer’ function, which enables the user to type in the word as found in the text and to be redirected to the correct lemma. The digital resource enables both Greek-Dutch searches and searches for the possible Greek equivalents of Dutch terms. This also makes it possible to explore the relation of semantic fields in Dutch and Greek. E.g., it is possible to locate all Greek words that have ‘courage’ as part of their definition. Furthermore, the digital resource makes it possible to locate different Greek words with the same etymological roots. And finally, the dictionary is linked to the website of the University of Chicago, where a comparison of all Greek-x dictionaries is supported. Here, one can enter a Greek word and be provided with the equivalents and definitions in all the dictionaries that are linked on this website.

  • MIGMAP: Detailed interactive mapping of migration in The Netherlands in the 20th century.

    MIGMAP is a web application that can show migration flow between Dutch municipalities. The user first chooses generation (forward or backward in time) and gender, while subsequently the migration map of The Netherlands related to an interactively pointed municipality (or other aggregation unit) is shown. The data underlying the migration maps originate from the first name selection from the Civil Registration, acquired by Utrecht University and the Meertens Institute in 2006. These concern 16 million records from persons with Dutch citizenship, alive in 2006, and in addition 6 million persons deceased before 2006, but mentioned in other records – mainly as parents. The records include identifiers by which family relations can be reconstructed. After considerable efforts in data clearing and reconstruction of older generations, the data provide an almost complete overview of the Dutch population, born after 1930, and a fairly good sample from the period 1880-1930 (>25%). The user will be given options to choose generation (places of birth of the current population, their parents, grandparents grand-grandparents, or starting with the persons born between 1880-1900: the current places of residence of their children, grandchildren), and gender. Each map will be made available as a .csv record with municipality number and percentage as fields, and thus can be used by users in correlation studies with other variables. Utrecht University and the Meertens Institute have the signed permission of the "Basisadministratie voor Persoonsgegevens en Reisdocumenten, The Hague" to use the data for scientific purposes. The migration maps present the data in an aggregated way, and do not violate privacy requirements (no individual can possibly be identified from the maps). However, the underlying data containing information about individual persons and their family relations cannot be made available for reasons of privacy.
    Bloothooft, G, Onland, D and Kunst, J.P. 2017. Mapping Migration across Generations. In: Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 351–360. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.29. License: CC-BY 4.0
    Ekamper, P. en Bloothooft, G. (2013), "Weg van je wortels. De afstand tussen overgrootouders en achterkleinkinderen", DEMOS 29, 2, p8.

  • TiCClops: Text-Induced Corpus Clean-up online processing system

    TICCL (Text Induced Corpus Clean-up) is a system that is designed to search a corpus for all existing variants of (potentially) all words occurring in the corpus. This corpus can be one text, or several, in one or more directories, located on one or more machines. TICCL creates word frequency lists, listing for each word type how often the word occurs in the corpus. These frequencies of the normalized word forms are the sum of the frequencies of the actual word forms found in the corpus. TICCL is a system that is intended to detect and correct typographical errors (misprints) and OCR errors (optical character recognition) in texts. When books or other texts are scanned from paper by a machine, that then turns these scans, i.e. images, into digital text files, errors occur. For instance, the letter combination `in' can be read as `m', and so the word `regeering' is incorrectly reproduced as `regeermg'. TICCL can be used to detect these errors and to suggest a correct form. Text-Induced Corpus Clean-up (TICCL) was developed first as a prototype at the request of the Koninklijke Bibliotheek - The Hague (KB) and reworked into a production tool according to KB specifications (currently at production version 2.0) mainly during the second half of 2008. It is a fully functional environment for processing possibly very large corpora in order to largely remove the undesirable lexical variation in them. It has provisions for various input and output formats, is flexible and robust and has very high recall and acceptable precision. As a spelling variation detection system it is to the developer’s knowledge unique in making principled use of the input text as possible source for target output canonical forms. As such it is far less domain-sensitive than other approaches: the domain is largely covered by the input text collection. TICCL comes in two variants: one with a classic CLAM web application interface, and one with the PhilosTEI interface.
    Reynaert, M. (2008). All, and only, the errors: More complete and consistent spelling and OCR-error correction evaluation. In: Proceedings of the Sixth International Language Resources and Evaluation (LREC’08), Marrakech, Morocco.
    Reynaert, M. (2010). Character confusion versus focus word-based correction of spelling and ocr variants in corpora. International Journal on Document Analysis and Recognition, pp 1-15, URL http://dx.doi.org/10.1007/s10032-010-0133-5

  • Usage

    The system here allows you to convert your book pages' images into editable text, presented in a particular text format called XML (eXtended Markup Language) of a particular type called Text-Encoding Initiative or TEI XML. This particular format was developed specifically for being able to mark-up or annotate the text you want to work on, i.e. to add all manner of further information to the actual text, e.g. to build a critical edition of it, which is most likely exactly what you want to do with your author's work.
    Betti, A, Reynaert, M and van den Berg, H. 2017. @PhilosTEI: Building Corpora for Philosophers. In: Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 379–392. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.32. License: CC-BY 4.0