The Semantic Biomedical Tagger (SBT) has a built-in capability to recognize 133 biomedical entity types and semantically link them to the knowledge base systems, in this case LinkedLifeData (LLD). The SBT can load entity names from the LLD service or any other RDF database with a SPARQL endpoint. The current version is preloaded with the latest release of LLD dataset. All URIs used by SBT are resolvable and can be opened by a web browser or a machine accessible API.
The details on the REST API for the Semantic Biomedical Tagger service are available on the Text Analytics page.
The SBT creates semantic annotations that have names (Annotation type) and features: class (URI), instance (URI), and string (instance label). Both URIs can be further explored in the LLD service.
The following table reveals the SBT annotation capabilities in terms of annotation types, number of labels and instances per type.
In our example we will use a very simple request for annotating just a couple of sentences of text from the following bio-medical article:
For the sake of clarity, if you annotate the sample text above with the demo UI of S4 you will see a result like this:
We are now ready to send a simple RESTful request to the S4 text analytics services using a simple command line tool like curl:
Lets go step-by-step through the sample code above:
The following example demonstrates the processing of Office documents (Word) as input for the S4 text anaylitics services. The result is in the format described in the next section.
API Key, Secret and service URL configured in the same way as in the previous example. The request payload comprises of two parts:
The RESTful request itself is performed via curl as multipart message. The HTTP request type should not be explicitly provided (curl configures it properly), however the JSON part 'meta' should explicitly set its content type ("type=application/json")
The full JSON response is available below.
Some important details:
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