class_docstr: A base class for combination of a graph pair into a single graph.
class_docstr_tok: ["A","base","class","for","combination","of","a","graph","pair","into","a","single","graph","."]
docstr: Process the combined mapped triples.
  
  :param mapped_triples: shape: (n, 3)
      the id-based merged triples
  :param alignment: shape: (2, m)
      the id-based entity alignment
  :param offsets: shape: (2, 2)
      the entity and relation offsets from merging
  
  :return:
      updated triples and alignment tensor, as well as parameters for updating label-to-id mappings
docstr_tok: ["Process","the","combined","mapped","triples",".",":","param","mapped_triples",":","shape",":","(","n",",","3",")","the","id-based","merged","triples",":","param","alignment",":","shape",":","(","2",",","m",")","the","id-based","entity","alignment",":","param","offsets",":","shape",":","(","2",",","2",")","the","entity","and","relation","offsets","from","merging",":","return",":","updated","triples","and","alignment","tensor",",","as","well","as","parameters","for","updating","label-to-id","mappings"]
code: def process(
      self,
      mapped_triples: MappedTriples,
      alignment: torch.LongTensor,
      offsets: torch.LongTensor,
  ) -> ProcessedTuple:
      """
      Process the combined mapped triples.
  
      :param mapped_triples: shape: (n, 3)
          the id-based merged triples
      :param alignment: shape: (2, m)
          the id-based entity alignment
      :param offsets: shape: (2, 2)
          the entity and relation offsets from merging
  
      :return:
          updated triples and alignment tensor, as well as parameters for updating label-to-id mappings
      """
      raise NotImplementedError
  
imports: import logging
  from abc import ABC, abstractmethod
  from collections import defaultdict
  from typing import Any, ClassVar, DefaultDict, Dict, Iterable, Mapping, NamedTuple, Optional, Sequence, Set, Tuple, Union
  import numpy
  import pandas
  import torch
  from class_resolver import ClassResolver
  from pandas.api.types import is_numeric_dtype, is_string_dtype
  from ...triples import CoreTriplesFactory, TriplesFactory
  from ...typing import COLUMN_HEAD, COLUMN_TAIL, EA_SIDE_LEFT, EA_SIDE_RIGHT, EA_SIDES, MappedTriples, TargetColumn
  from ...utils import format_relative_comparison, get_connected_components
label_desc: Use image node_id 2 for calling the GraphPairCombinator obj's underlying member method code with example usage: obj.process(mapped_triples, alignment, offsets) without return types