Unify docs and convert rst to ipynb

README.md

@@ -26,15 +26,19 @@ Please leave us [your feedback](https://forms.gle/i64fowQmiVhMMC7f9) on how we c
 
 **Models**
 
-[Named Entity Recognition](http://docs.deeppavlov.ai/en/master/features/models/NER.html) | [Intent/Sentence Classification](http://docs.deeppavlov.ai/en/master/features/models/classifiers.html) |
+[Named Entity Recognition](http://docs.deeppavlov.ai/en/master/features/models/NER.html) | [Intent/Sentence Classification](http://docs.deeppavlov.ai/en/master/features/models/classification.html) |
 
-[Question Answering over Text (SQuAD)](http://docs.deeppavlov.ai/en/master/features/models/SQuAD.html) | [Knowledge Base Question Answering](http://docs.deeppavlov.ai/en/master/features/models/kbqa.html)
+[Question Answering over Text (SQuAD)](http://docs.deeppavlov.ai/en/master/features/models/SQuAD.html) | [Knowledge Base Question Answering](http://docs.deeppavlov.ai/en/master/features/models/KBQA.html)
 
-[Sentence Similarity/Ranking](http://docs.deeppavlov.ai/en/master/features/models/neural_ranking.html) | [TF-IDF Ranking](http://docs.deeppavlov.ai/en/master/features/models/tfidf_ranking.html) 
+[Sentence Similarity/Ranking](http://docs.deeppavlov.ai/en/master/features/models/neural_ranking.html) | [TF-IDF Ranking](http://docs.deeppavlov.ai/en/master/features/models/tfidf_ranking.html)
 
-[Automatic Spelling Correction](http://docs.deeppavlov.ai/en/master/features/models/spelling_correction.html) | [Entity Linking](http://docs.deeppavlov.ai/en/master/features/models/entity_linking.html)
+[Syntactic Parsing](http://docs.deeppavlov.ai/en/master/features/models/syntax_parser.html) | [Morphological Tagging](http://docs.deeppavlov.ai/en/master/features/models/morpho_tagger.html)
 
-[Open Domain Questions Answering](http://docs.deeppavlov.ai/en/master/features/models/odqa.html) | [Russian SuperGLUE](http://docs.deeppavlov.ai/en/master/features/models/superglue.html)
+[Automatic Spelling Correction](http://docs.deeppavlov.ai/en/master/features/models/spelling_correction.html) | [Entity Extraction](http://docs.deeppavlov.ai/en/master/features/models/entity_extraction.html)
+
+[Open Domain Questions Answering](http://docs.deeppavlov.ai/en/master/features/models/ODQA.html) | [Russian SuperGLUE](http://docs.deeppavlov.ai/en/master/features/models/superglue.html)
+
+[Relation Extraction](http://docs.deeppavlov.ai/en/master/features/models/relation_extraction.html)
 
 **Embeddings**
 
@@ -179,7 +183,7 @@ from deeppavlov import evaluate_model
 model = evaluate_model(<config_path>, install=True, download=True)
 ```
 
-DeepPavlov also [allows](https://docs.deeppavlov.ai/en/master/features/python.html) to build a model from components for
+DeepPavlov also [allows](https://docs.deeppavlov.ai/en/master/intro/python.html) to build a model from components for
 inference using Python.
 
 ## License

deeppavlov/models/kbqa/utils.py

@@ -123,9 +123,11 @@ def correct_variables(query_triplets: List[str], answer_ent: List[str], query_in
             for j in range(len(triplet_elements)):
                 if triplet_elements[j] not in ent_var and triplet_elements[j].startswith("?"):
                     triplet_elements[j] = query_info["mid_var"]
+                    break
                 if triplet_elements[j].startswith("?") \
                         and triplet_elements[j] not in [query_info["mid_var"], query_info["unk_var"]]:
                     triplet_elements[j] = query_info["unk_var"]
+                    break
             query_triplets[i] = " ".join(triplet_elements)
             query_triplets[i] = query_triplets[i].replace(ent_var, query_info["unk_var"])
     return query_triplets
@@ -174,8 +176,11 @@ def make_sparql_query(query_info: Tuple[List[str], List[str], List[str], Dict[st
     query_triplets = [fill_slots(elem, entities, types, rels, delete_rel_prefix=True) for elem in query_triplets]
     query_triplets = correct_variables(query_triplets, answer_ent, query_info_dict)
     filled_queries = []
-    for triplets_p in list(itertools.permutations(query_triplets)):
-        filled_queries.append(query_from_triplets(triplets_p, answer_ent, query_info_dict))
+    if any(["qualifier" in filter_info_element for filter_info_element in filter_info]):
+        filled_queries.append(query_from_triplets(query_triplets, answer_ent, query_info_dict))
+    else:
+        for triplets_p in list(itertools.permutations(query_triplets)):
+            filled_queries.append(query_from_triplets(triplets_p, answer_ent, query_info_dict))
     return filled_queries