Search results

• VU University Diachronic News text Corpus

  The diachronic corpus has been brought in line with current standards and formats as used in the STEVIN Nederlandstalig Referentiecorpus (SoNaR, under development), which has been adapted to the more general FoLiA format (documented by Van Gompel, 2012). These standards and formats have been extended with new layers of annotation. As a result the corpus adheres to the current day CLARIN infrastructure.

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• OpenSONAR: a 500 MW reference corpus of Contemporary Written Dutch

  SoNaR is a 500-million-word reference corpus of contemporary written Dutch for use in different types of linguistic (incl. lexicographic) and HLT research and the development of applications. The STEVIN funded SoNaR project (2008-2011) built on the results obtained in the D-Coi and Corea projects which were awarded funding in the first call of proposals within the STEVIN programme. SONAR contains over 500 million words (i.e. word tokens) of full texts from a wide variety of text types including both texts from conventional media and texts from the new media. All texts except for texts from the social media (Twitter, Chat, SMS) have been tokenized, tagged for part of speech and lemmatized, while in the same set the Named Entities have been labelled. All annotations were produced automatically, no manual verification took place. The texts are enriched with several annotations (Part of Speech and lemma information) and are available as FoLiA xml files (folia.xml). The system relies on BlackLab server as back-end and WhiteLab as user-interface. OpenSONAR is an online application for exploration of and searching in the SoNaR corpus.

  van de Camp, M, Reynaert,MandOostdijk, N. 2017.WhiteLab 2.0: AWeb Interface for Corpus Exploitation. In: Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 231–243. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.19. License: CC-BY 4.0

  de Does, J, Niestadt, J and Depuydt, K. 2017. Creating Research Environments with BlackLab. In: Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 245–257. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.20. License: CC-BY 4.0

  Oostdijk, N., Reynaert, M., Hoste, V., Schuurman, I. (2013) The Construction of a 500 Million Word Reference Corpus of Contemporary Written Dutch in: Essential Speech and Language Technology for Dutch: Results by the STEVIN-programme (eds. P. Spyns, J. Odijk), Springer Verlag.

• CLARIN Concept Registry

  The CCR is a concept registry according to the W3C SKOS recommendation. It was chosen by CLARIN to serve as a semantic registry to overcome semantic interoperability issues with CMDI metadata and different annotation tag sets used for linguistic annotation. The CCR is part of the CMDI metadata infrastructure. The W3C SKOS recommendation, and the OpenSKOS implementation thereof, provides the means for ‘data-sharing, bridging several different fields of knowledge, technology and practice’. According to this model, each concept is assigned a unique administrative identifier, together with information on the status or decision-making process associated with the concept. In addition, concept specifications in the CCR contain linguistic descriptions, such as definitions and examples, and can be associated with a variety of labels. .

• CMDI to RDF conversion

  There is growing amount of on-line information available in RDF format as Linked Open Data (LOD) and a strong community very actively promotes its use. The publication of information as LOD is also considered an important signal that the publisher is actively searching for information sharing with a world full of new potential users. Added advantages of LOD, when well used, are the explicit semantics and high interoperability. But the problematic modelling by non-expert users offsets these advantages, which is a reason why modelling systems as CMDI are used. The CMDI2RDF project aims to bring the LOD advantages to the CMDI world and make the huge store of CMDI information available to new groups of users and at the same time offer CLARIN a powerful tool to experiment with new metadata discovery possibilities. The CMD2RDFservice was created to allow connection with the growing LOD world, and facilitate experiments within CLARIN merging CMDI with other, RDF based, information sources. One of the promises of LOD is the ease to link data sets together and answer queries based on this ‘cloud’ of LOD datasets. Thus in the enrichment and use cases part of the project we looked at other datasets to link to the CLARIN joint metadata domain. We used the WALS N3 RDF dump for one of the use cases. Although it is in the end relatively easy to go from a specific typological feature to the CMD records via a shared URI, it still showcased a weakness of the Linked Data approach. One has to carefully inspect the property paths involved. And in this case the path was broken as there was no clear way to go from the WALS feature data to the WALS language info except for extracting the WALS language code from the feature URI pattern and insert it the language URI pattern. This showcases that although the big LOD cloud shows potential for knowledge discovery by crossing dataset boundaries, design decisions in the individual datasets can still hamper algorithms and manual inspection is needed. The CMD2RDF service was developed at the TLA/MPI for Psycholinguistics and DANS and later moved to Meertens Institute where the expertise remains.

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• Texcavator End-user Manual

  WAHSP/BLAND has been succeeded by TexCavator: http://texcavator.surfsaralabs.nl/

  Texcavator enables a researcher to use full-text search on the newspaper archive of the Dutch Royal Library. On top of that, it allows for visualizations like word clouds, time lines and heat maps. It also provides services to enhance your search experience like filtering, stopword removal, normalization and stemming. Texcavator also gives access to ShiCo (Shifting Concepts), developed by Carlos Martinez Ortiz (NL eScience Center).ShiCo is a tool for visualizing time shifting concepts. We refer to a concept as the set of words which are related to a given seed word. ShiCo uses a set of semantic models (word2vec) spanning a number of years to explore how concepts change over time -- words related to a given concept at time t=0 may differ from the words related to the same concept at time t=n . Texcavator originated from the earlier text mining applications WAHSP and BiLand. During the Translantis project, the application was renamed to Texcavator and further developed by the UvA (Fons Laan). In May 2014, development was taken over by the Netherlands eScience Center (Janneke van der Zwaan). From April 2015 onwards, Texcavator was developed at the Digital Humanities lab of Utrecht University (Julian Gonggrijp and Martijn van der Klis). ShiCo was created in cooperation with the NL eScience Center (Carlos Martinez Ortiz).

  Snelders, S, Huijnen, P, Verheul, J, de Rijke, M and Pieters. T. 2017. A Digital Humanities Approach to the History of Culture and Science: Drugs and Eugenics Revisited in Early 20th-Century Dutch Newspapers, Using Semantic TextMining. In:Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 325–336. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.27. License: CC-BY 4.0

• MIMORE: Microcomparative Morphosyntax Research Tool

  With the MIMORE search engine one can search three databases together, with text strings, part of speech tags and syntactic variables. The researcher can combine categories and features into complex tags or use predefined tags. All categories and features are defined in ISOcat. Since all sentences have a location code, the morphosyntactic phenomena found in a set of sentences resulting from a search can be automatically plotted on a geographic map. It is possible to include more than one morphosyntactic phenomenon in one map, thus visualizing potential correlations between these phenomena. There is also a user-friendly function to export the data to a statistical program. The data in DynaSAND, the dynamic syntactic atlas of the Dutch dialects (http://www.meertens.knaw.nl/sand/ (link is external)), were collected between 2000 and 2005 by oral interviews (fieldwork and telephone) in about 300 locations across The Netherlands, Belgium and a small part of north-west France. Dialect speakers were asked to judge and/or translate some 150 test sentences. DynaSAND makes available the full recordings and transcriptions of these interviews. Together, the DynSAND data cover the syntactic variation in the Dutch language area in the left periphery of the clause (the complementizer system and complementizer agreement), variation in subject pronoun form depending on syntactic position, subject pronoun doubling, cliticization on YES/NO, the reflexive system, fronting constructions (Wh-clauses, relative clauses, topicalization), word order and morphological variation in verb clusters, negation and quantification. The data in DiDDD (Diversity in Dutch DP Design; http://www.meertens.knaw.nl/diddd/ (link is external)) were collected between 2005 and 2009 with oral and written interviews in about 200 locations in the Dutch language area, with a methodology highly parallel to DynaSAND. The data involve translations of and judgements on test sentences. For 29 interviews there are sound recordings which have been lined up with their transcriptions. The DIDDD data cover the morphosyntactic variation within nominal groups, in particular possessives, partitives, noun ellipsis, the demonstrative system, the numeral modification system, what-for constructions, quantitative er, adjectival inflection, negation and exclamatives. The data in GTRP (Goeman, Taeldeman, van Reenen Project; http://www.meertens.knaw.nl/mand/database/ (link is external)) were collected between 1979 and 2000 with oral interviews in about 600 locations in the Dutch language area. Informants were asked to translate words or short sentences. Part of the transcriptions have been lined up with the sound recordings. The morphological data in GTRP include plural forms of nouns, diminutives, gender on nouns and adjectives, comparatives, superlatives, verbal inflection including participles, subject, object and possessive pronouns.

  S. Barbiers, M. van Koppen, H. Bennis, N. Corver, MIcrocomparative MOrphosyntactic REsearch (MIMORE): Mapping partial grammars of Flemish, Brabantish and Dutch. Lingua Vol. 178, 5-31. doi:10.1016/j.lingua.2015.10.018

• VLO: The Virtual Language Observatory

  The VLO is a faceted browser that shows the metadata records harvested from within the CLARIN joint metadata domain. Next to that it also shows part of the Language Resource metadata that can be harvested from the OLAC domain. The Virtual Language Observatory (VLO) is meant to be the open market place where users can find metadata descriptions of all language resources and tools/services which we can harvest from any useful and trusted source. Currently VLO contains more than 230.000 resources and more than 400 tools already. Different user interfaces are maintained to allow users to find and select resources such as a GoogleEarth overlay for geographic browsing, a facetted browser for easy search and browsing along major criteria and a normal cata- logue. The VLO machinery is ready to harvest various types of metadata that is offered via the OAI-PMH pro- tocol. It currently is harvesting data from OLAC, DFKI Tool registry, DOBES, DELAMAN partners, MPI registry, ELRA catalogue and the CLARIN Language Resource and Technology inventory which was meant as a simple registry for resources and tools from CLARIN members. VLO is based on the principle that metadata needs to be open.

  Van Uytvanck, D., Stehouwer, H., and Lampen, L. (2012). Semantic metadata mapping in practice: The Virtual Language Observatory. In N. Calzolari (Ed.), Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC 2012), Istanbul, May 23rd-25th, 2012 (pp. 1029-1034). European Language Resources Association (ELRA).

• Taalportaal, the linguistics of Dutch, Frisian and Afrikaans online.

  Taalportaal (or Language Portal) is an interactive knowledge base about Dutch, Frisian and Afrikaans. It provides access to a comprehensive and authoritative scientific grammar for these three languages.

  van der Wouden, T, Bouma, G, van deCamp, M, van Koppen, M, Landsbergen, F and Odijk, J. 2017. Enriching a Scientific Grammar with Links to Linguistic Resources: The Taalportaal. In: Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 299–310. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.24. License: CC-BY 4.0

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• WIP: War in Parliament

  An advanced search engine for the OCR-ed scanned image collection of proceedings of the Dutch Hansard (Handelingen der Staten-Generaal 1930-1995). These proceedings are available as a fully annotated semi-structures dataset for historical and social science research. The output of the search engine can be restricted by speaker name, party, date range, and other criteria. References to the Second World War (WW II) have shaped political debate in the Netherlands for many decades. However, we have no systematic knowledge of why, how often, when, by whom or from which political party, and in which context, these references were made. Nor do we know the meanings politicians ascribed to the war years, the lessons the war was supposed to teach, and how all of this influenced political decision-making. WIP helps answering these questions and will help us better understand the complex legacies of WW II. The WIP project bridges the gap between historical and social science practices and the possibilities offered by using large corpora and language resources, in particular Clarin tools for Dutch. The dataset - de Handelingen der Staten-Generaal (Dutch Hansard) - are made compliant with Clarin, ISOCAT and ISO/TC 37/SC 4 standards. The search engine for this dataset uses an intuitive and powerful query language based on XPath, and its output can be fed directly into further analysis programs like SPSS. Integrating this technology with important historical research questions will directly contribute to new and innovative ways of writing about history. The search engine results can be exported in a CSV-format (comma seperated values). This makes it easy to calculate statistics offline from a result set and apply further filters.

  Marx, M. (2011), Oorlog in de Kamer, NRC, March 3, 2011

  ‘Waarom politici graag over de oorlog praten’, NRC-Handelsblad, 25 februari 2011

  ‘Zoekmachine vindt relevante WO2-verwijzingen in Handelingen der Staten Generaal. Dat doet denken aan de oorlog’, in: E-data & research, Jaargang 6, nummer 2, oktober 2011 http://www.edata.nl/0602_011011/pdf/0602_011011_1.pdf

  ‘NIOD ontwikkelt zoekmachine die verwijzingen naar de oorlog opspoort’, in: Informatie Professional. Vakblad voor informatiewerkers, nr. 11 (2011)

  L. Buitinck en M. Marx (2012), ‘Two-stage named entity recognition using averaged perceptrons’, in: Proc. NLDB 2012, pp. 171-176

• Dupira; the Dutch Parser for IR Applications

  Dupira is a rule-based parser, generated by means of the AGFL parser generator from the Dupira grammar, lexicon and fact tables. By means of transductions which are specified in the grammar (and can be modified), the parser transduces sentences to dependency graphs. Dupira was developed for practical applications in Information Retrieval and for Information Systems needing a Natural Language interface. Its intended users are computer scientists and computer professionals rather than linguists.

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