Towards Practical Semantic Interoperability in NLP Platforms (2022)

Abstract: Interoperability is a necessity for the resolution of complex tasks that require the interconnection of several NLP services. This article presents the approaches that were adopted in three scenarios to address the respective interoperability issues. The first scenario describes the creation of a common REST API for a specific platform, the second scenario presents the interconnection of several platforms via mapping of different representation formats and the third scenario shows the complexities of interoperability through semantic schema mapping or automatic translation.

## introduction for a long time, the development of nlp infrastructures or platforms that provide a larger number of nlp services was not practically feasible. in recent years this has changed with the appearance of new technologies, especially containerisation and microservices. the main advantage of these technologies is that they enable individual development as well as easy deployment and execution of nlp services, thus facilitating their re-use into one's own computing system/environment. however, individual development of tools especially when distributed among different organisations gives rise to interoperability @xcite issues, e. g., the services are developed without a common data model (exchange format), with different technologies and apis (grpc, rest) etc. in short, the services cannot be easily combined. achieving interoperability becomes more complex the greater the number of individual services involved. for a further analysis of interoperability challenges encountered and potential methods of mitigation we look at three scenarios of different complexity. from simple to more challenging, these are: this article presents the work carried out so far to address the three interoperability scenarios mentioned above. the interoperability mechanisms developed in the european language grid (elg) platform 3 to make its heterogeneous and growing set of tools and services compatible (common api specification) and interconnectable (python sdk) are described in section 2. the interoperability mechanisms implemented in the qurator 4 and speaker 5 projects (in addition @xmath0.0" @xmath1: example of annotations made by two services using the same format and different semantic schema lynx foot_5 ) to mainly cover scenario 2, and minimally scenario 3 (workflow manager) are presented in section 3. the proposed solution to solve scenario 3 as generically as possible is introduced in section 4. section 5 presents related work. finally, section 6 concludes the article and sketches directions for future work. ## interoperability through common api specification (scenario 1) the european language grid (elg) platform addresses interoperability by forcing the nlp services to use a predefined format. this corresponds to the first interoperability scenario described in section 1. ## intra-platform interoperability through format mapping (scenario 2) as presented in the introduction, interoperability scenario 2 occurs when two (or more) services (from the same or different platforms) use different formats (json, xml, rdf, etc.) for input and/or output of the information processed/to be processed. the distinctive feature of this scenario is that the number of formats is limited, which allows the manual implementation of interoperability between all of them. this means that format conversions are accomplished through manually defined rules for each conversion step. in the following, we present all the implementations made to achieve interoperability in this scenario through a workflow manager (moreno-schneider et al., 2020). 11 helsinkinlp -opus-mt (eng-gmw): english-german machine translation https://live.european-language-grid.eu/ catalogue/tool-service/9183 12 marytts -german male (dfki-pavoque-neutralhsmm) https://live.european-language-grid.eu/catalogue/ tool-service/4842 ## semantic interoperability between nlp services (scenario 3) the last scenario pursues the interoperability of nlp services that use different semantic schemas. the term semantic schema refers to the way information is annotated in a document and to what semantic information it is related, i. e., how it is represented in a document that a word is a named entity and of what type. foot_11 ## conclusions and future work we propose an approach to achieve semantic interoperability in nlp services in the most generic way possible. to reach this goal, three scenarios with distinct interoperability needs are described, for which different interoperability solutions have been created. the first experiments with a language model (gpt-3) are promising, but also show their limitations. in terms of future work, we will focus mainly on the development of methods that allow us to successfully implement this automatic mapping.