class_docstr: Class for ranking of paths in subgraph
class_docstr_tok: ["Class","for","ranking","of","paths","in","subgraph"]
code: def preprocess_ranking_input(self, question, answers):
      l_questions, l_rels, l_rels_labels, l_cur_answers = [], [], [], []
      l_entities, l_types, l_sparql_queries, l_triplets, l_confs = (
          [],
          [],
          [],
          [],
          [],
      )
      for ans_and_rels in answers:
          answer, sparql_query, confidence = "", "", []
          entities, types, rels, rels_labels, triplets = (
              [],
              [],
              [],
              [],
              [],
          )
          if ans_and_rels:
              rels = [
                  rel.split("/")[-1]
                  for rel in ans_and_rels["relations"]
              ]
              answer = ans_and_rels["answers"]
              entities = ans_and_rels["entities"]
              types = ans_and_rels["types"]
              sparql_query = ans_and_rels["sparql_query"]
              triplets = ans_and_rels["triplets"]
              confidence = ans_and_rels["output_conf"]
              rels_labels = []
              for rel in rels:
                  if rel in self.rel_q2name:
                      label = self.rel_q2name[rel]
                      if isinstance(label, list):
                          label = label[0]
                      rels_labels.append(label.lower())
          if rels_labels:
              l_questions.append(question)
              l_rels.append(rels)
              l_rels_labels.append(rels_labels)
              l_cur_answers.append(answer)
              l_entities.append(entities)
              l_types.append(types)
              l_sparql_queries.append(sparql_query)
              l_triplets.append(triplets)
              l_confs.append(confidence)
      return (
          l_questions,
          l_rels,
          l_rels_labels,
          l_cur_answers,
          l_entities,
          l_types,
          l_sparql_queries,
          l_triplets,
          l_confs,
      )
  
file_path: DeepPavlov/deeppavlov/models/kbqa/rel_ranking_infer.py
imports: from logging import getLogger
  from typing import Tuple, List, Any, Optional
  from scipy.special import softmax
  from deeppavlov.core.common.chainer import Chainer
  from deeppavlov.core.common.file import load_pickle, read_json
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.models.component import Component
  from deeppavlov.core.models.serializable import Serializable
  from deeppavlov.models.kbqa.sentence_answer import sentence_answer
  from deeppavlov.models.kbqa.wiki_parser import WikiParser
label_desc: Use image node_id 5 for calling the RelRankerInfer obj's underlying member method code with example usage: obj.preprocess_ranking_input(question, answers) and returns: l_questions,  l_rels,  l_rels_labels,  l_cur_answers,  l_entities,  l_types,  l_sparql_queries,  l_triplets,  l_confs