def resolve_compare_function(n1, n2, d=_dict):
if (n1['type'], n2['type']) in d:
v = d[(n1['type'], n2['type'])]
if type(v) == dict:
return resolve_compare_function(father(n1), father(n2), d=v)
elif type(v) == list:
return d[(n2['type'], n1['type'])]
else:
raise TypeError("Only nested dicts or lists are allowed")
else:
return []
def _rarity_node_to_source(node):
rar_i = []
M = count['M']
g = node['graph']
while node['id'] != 'source':
try:
# Subtract __max__ key
N = len(count['node'][node['type']]) - 1
rar_i.append((M - N) / M)
except KeyError:
return None
# Feature step
father_node = father(node)
linking_feature_type = g[father_node['id']][
node['id']]['generating_function']
try:
N = count['feature'][linking_feature_type]
rar_i.append((M - N) / M)
except KeyError:
return None
node = father_node
return rar_i
def trace(n):
tr = []
while True:
tr.insert(0, n['type'])
father_n = father(n)
if father_n is not None:
tr.insert(0, n['graph'][father_n['id']][n['id']]['type'])
n = father_n
else:
break
return tr
def phrase_recursive(n, node_type_level, search_for):
if search_for in node_type_level:
return node_type_level[search_for]
for k in node_type_level.keys():
k_as_tuple = (k,) if type(k) == str else k
if n['type'] in k_as_tuple:
edge_type_level = node_type_level[k]
if search_for in edge_type_level:
return edge_type_level[search_for]
if father(n) == None:
return None
else:
gen_function = n['graph'][father(n)['id']][n['id']]['generating_function']
for k in edge_type_level.keys():
k_as_tuple = (k,) if type(k) == str else k
if gen_function in k_as_tuple:
node_type_level = edge_type_level[k]
return phrase_recursive(father(n), node_type_level, search_for)
def shortness_score(segue):
length = 0
for node in [segue['n1'], segue['n2']]:
node = segue['n1']
while True:
node_father = father(node)
generating_function = node['graph'][node_father['id']][node['id']]['generating_function']
if generating_function == 'init':
length += 1
break
func = getattr(globals()[generating_function], generating_function)
length += 1 if 'entailed' not in func.__annotations__ else 0
node = node_father
shortness = 2/length
return shortness
def _popularity_node_to_source(node):
pop_i = []
while node['id'] != 'source':
id_node = craft_id_node_graph(node)
if node['type'] in count['node']:
try:
node_edgeset = count['node'][node['type']][id_node]
except KeyError:
node_edgeset = np.inf
meadian_edgeset_actual_type = count['node'][node['type']]['__meadian__']
pop_i.append(min(1, node_edgeset/meadian_edgeset_actual_type))
else:
return None
node = father(node)
return pop_i
def _popularity_node_to_source(node):
pop_i = []
while node['id'] != 'source':
id_node = craft_id_node_graph(node)
if node['type'] in count['node']:
try:
node_edgeset = count['node'][node['type']][id_node]
except KeyError:
node_edgeset = 0
max_edgeset_actual_type = count['node'][
node['type']]['__max__']
pop_i.append(node_edgeset / max_edgeset_actual_type)
else:
return None
node = father(node)
return sum(pop_i) / len(pop_i)
def get_template_relationship(n):
with open(f"{preprocessed_dataset_path}/textual_templates_artist_relationships.json") as f:
d = json.load(f)
d = {k: inner_dict[k] for inner_dict in d.values() for k in inner_dict.keys()}
template = d[n['graph'][father(n)['id']][n['id']]['type']]['preprocessed']
return template
def eligible_nodes_filter(self, g, node, func):
"""Used to eventually filter out nodes that would otherwise be considered as applicable to some features.
Useful to limit the graph growth.
Active filters:
-avoid infinite loops
-do not expand nodes that originate from an artist relationship
-if the feature is entailment, then apply to a synset only if it directly discend from a word
-if the feature is member_holonyms, then apply to a synset only if it directly discend from a word
-if the feature is member_meronyms, then apply to a synset only if it directly discend from a word
-if the feature is part_holonyms, then apply to a synset only if it directly discend from a word
-if the feature is part_meronyms, then apply to a synset only if it directly discend from a word
-if the feature is substance_holonyms, then apply to a synset only if it directly discend from a word
-if the feature is substance_meronyms, then apply to a synset only if it directly discend from a word
-if the feature is synset_also_sees, then apply to a synset only if it directly discend from a word
-if the feature is synset_attributes, then apply to a synset only if it directly discend from a word
-if the feature is synset_similar_tos, then apply to a synset only if it directly discend from a word
-if the feature is synset_verb_groups, then apply to a synset only if it directly discend from a word
-if the feature is hypernyms, then apply to a synset only if it directly discend from a word
-if the feature is hyponyms, then apply to a synset only if it directly discend from a word
Args:
g (ngx Graph): Graph to be built
node (ngx Node): The eligible node to keep or filter out
func (function): Feature to which node would be eventually fed
Returns:
Bool: True if keep it, False if discard it
"""
# a => b is equivalent to not a or b
if g[father(node)['id']][node['id']]['generating_function'] != func.__name__ and \
g[father(node)['id']][node['id']]['generating_function'] != 'artist_relationships' and \
(not func.__name__ == 'entailment' or father(node)['type'] == 'word') and \
(not func.__name__ == 'member_holonyms' or father(node)['type'] == 'word') and \
(not func.__name__ == 'member_meronyms' or father(node)['type'] == 'word') and \
(not func.__name__ == 'part_holonyms' or father(node)['type'] == 'word') and \
(not func.__name__ == 'part_meronyms' or father(node)['type'] == 'word') and \
(not func.__name__ == 'substance_holonyms' or father(node)['type'] == 'word') and \
(not func.__name__ == 'substance_meronyms' or father(node)['type'] == 'word') and \
(not func.__name__ == 'synset_also_sees' or father(node)['type'] == 'word') and \
(not func.__name__ == 'synset_attributes' or father(node)['type'] == 'word') and \
(not func.__name__ == 'synset_similar_tos' or father(node)['type'] == 'word') and \
(not func.__name__ == 'synset_verb_groups' or father(node)['type'] == 'word') and \
(not func.__name__ == 'hypernyms' or father(node)['type'] == 'word') and \
(not func.__name__ == 'hyponyms' or father(node)['type'] == 'word'):
return True
else:
return False