Search results

• 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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• 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

• 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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