code: def _run_coref(
      topics: Topics,
      resources: SievesContainerInitialization,
      eval_type: str,
  ) -> List[Clusters]:
      """
      Running Cross Document Coref on Entity mentions
      Args:
          resources: (SievesContainerInitialization) resources for running the evaluation
          topics   : The Topics (with mentions) to evaluate
  
      Returns:
          Clusters: List of topics and mentions with predicted cross doc coref within each topic
      """
      clusters_list = list()
      for topic in topics.topics_list:
          sieves_list = get_run_system(topic, resources, eval_type)
          clusters = sieves_list.run_deterministic()
          clusters.set_coref_chain_to_mentions()
          clusters_list.append(clusters)
  
      return clusters_list
  
file_path: nlp-architect/nlp_architect/models/cross_doc_sieves.py
imports: import logging
  from typing import List
  from nlp_architect.common.cdc.cluster import Clusters
  from nlp_architect.common.cdc.topics import Topics
  from nlp_architect.models.cross_doc_coref.system.sieves.run_sieve_system import get_run_system
  from nlp_architect.models.cross_doc_coref.system.sieves_container_init import SievesContainerInitialization
label_desc: Use image node_id 3 for calling a global function with example usage: _run_coref(topics, resources, eval_type) and returns: clusters_list