Mention pynif, add archived link to NLP2RDF dashboard

docs/classifier_training.rst

@@ -10,7 +10,7 @@ Getting a NIF dataset
 ---------------------
 
 Training requires access to a dataset encoded in `NIF (Natural Language Interchange Format) <https://github.com/dice-group/gerbil/wiki/NIF>`__.
-Various such datasets can be found at the `NLP2RDF dashboard <http://dashboard.nlp2rdf.aksw.org/>`__.
+Various such datasets can be found at the `NLP2RDF dashboard <http://dashboard.nlp2rdf.aksw.org/>`__ (`archived version <https://web.archive.org/web/20190913203545/http://dashboard.nlp2rdf.aksw.org/>`_).
 The NIF dataset is required to use Wikidata entity URIs for its annotations. Here is an example of what it looks like in the flesh::
 
    <https://zenodo.org/wd_affiliations/4> a nif:Context,
@@ -29,13 +29,17 @@ The NIF dataset is required to use Wikidata entity URIs for its annotations. Her
       itsrdf:taIdentRef <http://www.wikidata.org/entity/Q30> .
 
 
+Converting an existing dataset from a custom format to NIF can be done using the `pynif <https://github.com/wetneb/pynif>`_ Python library.
+This library can be used to generate and parse NIF datasets with a simple API.
+
 Annotating your own dataset
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 If you want to annotate your own dataset, you could use an existing annotator such as `NIFIFY <https://github.com/henryrosalesmendez/NIFify_v2>`__ (although it currently does not seem to handle large datasets very well).
 
-Converting an existing dataset to Wikidata
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Converting an existing NIF dataset to Wikidata
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 If you have an existing dataset with URIs pointing to another knowledge base, such as DBpedia, you can convert it to Wikidata.
 This will first require translating existing annotations, which can be done automatically with tools such as `nifconverter <https://github.com/wetneb/nifconverter>`__. Then comes the harder part: you need to annotate any mention of an entity which is not