Major performance improvements and fixes

Major performance improvements, more options for input/output formats,
handling long documents

[NEW] Changed database schema to v7 (need to download the new
repository). Gives speedup.
[NEW] Entities are now identified with knowledge base and identifier
[NEW] Entity metadata and JSON contains depiction URLs (from DBpedia
3.9)
[NEW] CommandLineDisambiguator writes HTML and JSON
[NEW] CommandLineDisambiguator takes strings from command line as input
(use -s -i "Text Input")
[NEW] Adding models for English Stanford NLP tools for caseless POS and
NER (e.g. for tweets)
[NEW] Mention comes with a set of normalized forms that are used to
query the dictionary for candiates and are different from the textual
representation of the mention
[NEW] Updated JSON format: adding allEntities and allTypes aggregate
fields, added kbIdentifier method for types
[NEW] Long document handling: fixed length text splitting and result
reconciliation. Length of split is configurable in aida.properties
[NEW] Web service can now be configured for maximum concurrent
disambiguation threads (see
src/mpi/aida/service/web/webapp/WEB-INF/web.xml for the configuration
parameters)
[NEW] More heuristics for identifying easy mentions. Gives speedup.
[NEW] NER architecture is now more pluggable
[NEW] Added caching for entity-keyphrase-weight data. Configure in the
aida.properties (entitiesCacheSize). Optional prefilling of the cache
by setting preloadEntityContexts to true (works only in web service).

[CHANGE] Default disambiguation configs now do thresholding on
low-confidence mentions
[CHANGE] Using HikariCP as database connector
[CHANGE] Java7 is now required
[CHANGE] Updated to Stanford CoreNLP 3.3.1

[FIX] General performance improvements and bug fixes