Add learning phase to shallow (1 level) nested structures.

naive-nlu/knowledge_evaluation.py

@@ -12,9 +12,33 @@ def resolve(knowledge_base, elements, value):
     return value
 
 
+# TODO: improve typing
+def infer_type(result):
+    if isinstance(result, bool):
+        return "bool"
+    elif isinstance(result, int):
+        return "int"
+
+    else:
+        raise Exception("Unknown type for value: {}".format(result))
+
+
+def get_subquery_type(knowledge_base, atom):
+    subquery_result = integrate_information(knowledge_base,
+                                            {
+                                                "parsed": atom,
+                                                "elements": [],
+                                            })
+    assert (subquery_result is not None)
+    result = subquery_result.getter()
+
+    result_type = infer_type(result)
+    return result_type
+
+
 def property_for_value(knowledge_base, value):
-    print(value)
-    print(knowledge_base[value])
+    # print(value)
+    # print(knowledge_base[value])
     return knowledge_base[value]['as_property']
 
 
@@ -27,6 +51,11 @@ def modifiable_property_from_property(prop, path, value):
         nonlocal prop, path, value
         prop[path] = value
 
+    return ModifiableProperty(
+        getter=getter,
+        setter=setter,
+    )
+
 
 def exists_property_with_value(knowledge_base, elements, subj, value):
     subj = resolve(knowledge_base, elements, subj)
@@ -50,6 +79,7 @@ def modifiable_element_for_existance_in_set(container, set_name, element):
     def setter():
         nonlocal container, set_name, element
         return container[set_name].add(element)
+
     return ModifiableProperty(
         getter=getter,
         setter=setter,