doc/HIGHLEVEL.md: Theory docs on the extra Evidence Gathering pipeline stage
TODO: More ideas on datasets to test
.gitignore: Add some extra entries
Initial implementation of DBpedia structured search

DBpedia relations of concept clues are converted to candidate answers,
with LATs matching the property names. Very naive.
answer.FocusGenerator: Dirty fix for unsanitized inputs from DBpedia
LATMatchTyCor: Actually generate AF_TyCorADBpRelation
AnswerScoreLogistic: Retrained with updated model
Merge remote-tracking branch 'origin/dbpans' into dbpans
Merge branch 'dbpans' of github.com:brmson/yodaqa into dbpans
Generate AF_TyCorA<origin> features only in case of precise hit

It seems that the wordnet-based generalization is pretty dangerous,
matching even way too unrelated things together and in result making
these features way too coarse otherwise.
AnswerScoreLogistic: Retrained with updated model
doc/HIGHLEVEL.md: Update the pipeline flow summary
LATByDBpedia: Produce a debug print only when we have something to report
Fix DKpro version at 1.7.0, just released
LATByFocus: Generate LAT for W- words with specificity 0.0

Previously, we lowered this to avoid ClueLAT. Now, we solve that by
generating instances of a new subclass ImplicitQLAT.
Passage TyCor: Add debug prints tied to type coercion happenning
AnswerGSHook: New property cz.brmlab.yodaqa.csv_answer to generate answer feature breakdowns, one CSV per question
DBpediaRelationPrimarySearch: Do not perform passage tycor

This would always happen the way we compose the title.
answer LATBy*: Do not sum up the LATFeature values, just set to 1.0 once

Our LAT features would represent as many times as we generated any hits,
reaching even 30 or 40 for dbpedia or wninstance sometimes. These
features should be just binary, though.
AnswerScoreLogistic: Retrained with updated model