Mapping G erma N et for the Semantic Web using O nto L ex-Lemon (2023)

Abstract: GermaNet is a large lexical-semantic net that relates German nouns, verbs, and adjectives semantically. The word net has been manually constructed over the last 25 years and hence presents a high-quality, valuable resource for German. While GermaNet is maintained in a Postgres database, all its content can be exported as an XML-based serialisation. Recently, this XML representation has been converted into RDF, largely by staying close to GermaNet’s principle of arrangement where lexunits that share the same meaning are grouped together into so-called synsets. With each lexical unit and synset now globally addressable via a unique resource identifier, it has become much easier to link together GermaNet entries with other lexical and semantic resources. In terms of semantic interoperability, however, the RDF variant of GermaNet leaves much to be desired. In this paper, we describe yet another conversion from GermaNet’s XML representation to RDF. The new conversion makes use of the OntoLex-Lemon ontology, and therefore, presents a decisive step toward a GermaNet representation with a much higher level of semantic interoperability, and which makes it possible to use GermaNet with other wordnets that already support this conceptualisation of lexica.

## introduction germanet was conceived in the mid-nineties (hamp and feldweg, 1997) and soon became the largest lexical-semantic wordnet for german. while it is still maintained as a relational database, it profited from quite a few format conversions in the meantime. with the wide adoption of the data interchange format xml, germanet's internal data representation -it is represented as a collection of relational database tables -was reformalized in terms of dtd-based document types. four dtds were defined: for synsets and their lexical unit children, for lexical and conceptual relations between them, for mapping germanet via the interlingual index to the princeton wordnet (miller, 1995; fellbaum, 1998), and for enriching germanet entries with wiktionary paraphrases. @xcite the current distribution of germanet provides both the database dump as well as an xml serialisation with xml documents that adhere to the dtd, and hence are syntactically valid. in total, the distribution encompasses 54 files (23 files for nouns, 15 files for verbs, and 16 files for adjectives). each file name encodes the word category and the semantic class of the synsets they contain. @xcite for each of the three word classes, there is also an xml file which encodes wiktionary entries, and there is a single file for the xml encoding of the interlingual index and another file to encode the conceptual and lexical relations. the single source of truth for germanet, however, is the postgres-based database. a specialpurpose tool called gernedit is used to edit and extend the german wordnet (henrich and hinrichs, 2010a). programming apis in java and python are available to access all germanet information programmatically. @xcite users without a usage licence for germanet can use the web-based rover application to explore germanet content. with rover, users can also calculate and visualize the semantic relatedness between any two given synsets. the latest version of germanet (release 17.0, april 2022) has about 205,000 lexical units and 159,514 synsets. there are 1,29 lexical units per @xcite in the eurowordnet framework (vossen, 1998) (see https://archive.illc.uva.nl/eurowordnet ), about 28,500 concepts from germanet have been linked to princeton wordnet(r) 2.0. we have used mappings from wordnet(r) 2.0 to wordnet(r) 3.0 provided by the nlp group of the universitat politècnica de catalunya to link germanet synsets to wordnet(r) 3.0. the mapping to wordnet(r) 3.0 was created automatically thus 100% accuracy of those mappings cannot be guaranteed. germanet already has some substantial linking to external data sources such as 28,564 pointers to the interlingual index and 29,546 links to wiktionary. note that any linking to external data sources is established through "local" identifiers only so that contextual information (say, this is an identifier in princeton wordnet 2.0) is required to resolve or look-up such linkages. it is worth pointing out that germanet has also been converted to the lexical markup framework (lmf, see (vossen et al., 2013)), which is discussed in (henrich and hinrichs, 2010b). recently, we have converted germanet's xml serialisation of its database into rdf (zinn et al., 2022). the conversion stayed close to germanet's conceptualisation of organising lexical-semantic nets (see sect. 2). while our conversion of ger-manet into rdf comes with no information loss, it ignores the work of others that aim at defining a standard for the description of wordnets. one such standard for representing wordnets is the ontolex-lemon conceptualisation foot_0 , which we briefly describe in sect. 3. in sect. 4, we show how we converted germanet's xml serialisation to the ontolex-lemon format and that most but not all of germanet content can be expressed in terms of this ontology. the conclusion and future work is discussed in sect. 5. ## conclusion and future work there have been two prominent translations of princeton wordnet into rdf (graves and gutierrez, 2006; van assem et al., 2006), but there is only one that uses the lemon vocabulary (mccrae et al., 2014). in this paper, we have described our conversion of germanet's xml format to a rdf representation that makes use of the ontolex-lemon conceptualisation, hence mirroring the work of mc-crae and colleagues for germanet. this makes it possible for germanet to be part of a linked data cloud that combines rich linguistic information from various, high-quality resources. in the near future, we will complement our conversion to include a more detailed representation of nominal compounds, and we still have to tackle the issue of representing syntactic frame information using the lexinfo vocabulary. the aim is to replace, whenever possible, our local vocabulary (in the namespace gn) with well-known terminology well-defined elsewhere. in this regard, germanet is monitoring recent developments in the global wordnet formats (mccrae et al., 2021). hence, our rdf version of germanet should not be considered final (yet) but open to change in the future. future work includes linking germanet with other rdf-based resources. in part, this is already done, as we have seen with the introduction of the ili link into the rdf-based princeton wordnet. at the time of writing, our germanet resource identifiers are not yet web-resolvable. in the future, an http request to, say, https://uni-tuebingen. de/germanet/v17/ei-n , will return the top left part of fig. 4 . rover, a web-based user interface for the exploration and visualization of germanet data (hinrichs et al., 2020) is currently using the xml representation and the java api in the back-end. in the future, we would like to experiment with using a back-end that executes sparql queries on the triple store. germanet is free for academic users with a signed license. @xcite for licence holders, both the database and the xml export are included in the data download. @xcite in the future, licence holders will also be able to obtain the rdf export of germanet. for accessing rdf-data via the web, we will follow our technical solution taken for our web-based rover application: a sign-in via the clarin service provider federation will allow users to authenticate as academic user, and subsequently, make use of the sparql endpoint to germanet. the main reason for having an rdf-based representation of germanet, however, is to unleash its potential when properly linked to other high-quality lexical sources. in the context of the text+ project, it is our aim to link germanet with the dwds dictionary of the german language @xcite and also with the leipzig corpora collection foot_9 . there are plans to convert both resources into rdf, which would allow the creation of a linked data cloud for the german language. in addition, we plan to link ger-manet to the lexicographical data of wikidata @xcite . mapping location entities of one dataset to the locations of another dataset is relatively straightforward. in general, the main task to properly link together nodes from different rdf graphs is -essentially -a word disambiguation task. our work will build upon henrich et al. (2014b), where ger-manet senses were linked to wiktionary senses, and henrich et al. (2014a), where word senses in germanet were linked with those in the dwds dictionary of the german language. the linking task will be supported by the webcage corpus (henrich et al., 2012).