class_docstr: A processing interface for tokenizing a string.
  Subclasses must define ``tokenize()`` or ``tokenize_sents()`` (or both).
class_docstr_tok: ["A","processing","interface","for","tokenizing","a","string",".","Subclasses","must","define","``","tokenize","(",")","``","or","``","tokenize_sents","(",")","``","(","or","both",")","."]
docstr: Apply ``self.span_tokenize()`` to each element of ``strings``.  I.e.:
  
      return [self.span_tokenize(s) for s in strings]
  
  :yield: List[Tuple[int, int]]
docstr_tok: ["Apply","``","self.span_tokenize","(",")","``","to","each","element","of","``","strings","``",".","I.e",".",":","return","[","self.span_tokenize","(","s",")","for","s","in","strings","]",":","yield",":","List","[","Tuple","[","int",",","int","]","]"]
code: def span_tokenize_sents(
      self, strings: List[str]
  ) -> Iterator[List[Tuple[int, int]]]:
      """
      Apply ``self.span_tokenize()`` to each element of ``strings``.  I.e.:
  
          return [self.span_tokenize(s) for s in strings]
  
      :yield: List[Tuple[int, int]]
      """
      for s in strings:
          yield list(self.span_tokenize(s))
  
file_path: nltk/nltk/tokenize/api.py
imports: from abc import ABC, abstractmethod
  from typing import Iterator, List, Tuple
  from nltk.internals import overridden
  from nltk.tokenize.util import string_span_tokenize
label_desc: Use image node_id 4 for calling the TokenizerI obj's underlying member method code with example usage: obj.span_tokenize_sents(strings) without return types