def answer(self):
'''
Answer the question.
Returns the answer struct, something along the lines of:
https://docs.google.com/document/d/1O6_sVSdSjgMmXacyI44JJfEVQLATagal9ydWLBgi-vE
'''
# get all subgraphs relevant to the question from the knowledge graph
database = KnowledgeGraph()
subgraphs = database.query(
self) # list of lists of nodes with 'id' and 'bound'
G = database.getGraphByLabel(self.id)
del database
# compute scores with NAGA, export to json
pr = ProtocopRank(G)
score_struct, subgraphs = pr.report_scores_dict(
subgraphs) # returned subgraphs are sorted by rank
out_struct = []
for substruct, subgraph in zip(score_struct, subgraphs):
graph = UniversalGraph(nodes=substruct['nodes'],
edges=substruct['edges'])
graph.merge_multiedges()
graph.to_answer_walk(subgraph)
out_struct += [
{'nodes':graph.nodes,\
'edges':graph.edges,\
'score':substruct['score']},
]
score_struct = out_struct
for i in range(len(score_struct)):
# score_struct[i]['edges'] = UniversalGraph.mergeMultiEdges(score_struct[i]['edges'])
score_struct[i]['info'] = {
'name': AnswerSet.constructName(score_struct[i])
}
max_results = 1000
if len(score_struct) > max_results:
return score_struct[:max_results]
else:
return score_struct
