spyCyとGiNZAがインストールできないエラーの解決方法

Question

前提

Pythonで学ぶテキストマイニング入門（2022; シーアンドアール研究所）で載っているcodeでMecabを使えるように練習している者です。
spyCyとGiNZAをPythonで実行できるようにする作業で、エラーが発生してしまいました。

実現したいこと

エラーの改善

発生している問題・エラーメッセージ

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_6896\3693895956.py in <module>
      1 import spacy
----> 2 nlp = spacy.load("ja_ginza")

~\anaconda3\lib\site-packages\spacy\__init__.py in load(name, vocab, disable, enable, exclude, config)
     52     RETURNS (Language): The loaded nlp object.
     53     """
---> 54     return util.load_model(
     55         name,
     56         vocab=vocab,

~\anaconda3\lib\site-packages\spacy\util.py in load_model(name, vocab, disable, enable, exclude, config)
    430             return get_lang_class(name.replace("blank:", ""))()
    431         if is_package(name):  # installed as package
--> 432             return load_model_from_package(name, **kwargs)  # type: ignore[arg-type]
    433         if Path(name).exists():  # path to model data directory
    434             return load_model_from_path(Path(name), **kwargs)  # type: ignore[arg-type]

~\anaconda3\lib\site-packages\spacy\util.py in load_model_from_package(name, vocab, disable, enable, exclude, config)
    466     """
    467     cls = importlib.import_module(name)
--> 468     return cls.load(vocab=vocab, disable=disable, enable=enable, exclude=exclude, config=config)  # type: ignore[attr-defined]
    469 
    470 

~\anaconda3\lib\site-packages\ja_ginza\__init__.py in load(**overrides)
      8 
      9 def load(**overrides):
---> 10     return load_model_from_init_py(__file__, **overrides)

~\anaconda3\lib\site-packages\spacy\util.py in load_model_from_init_py(init_file, vocab, disable, enable, exclude, config)
    647     if not model_path.exists():
    648         raise IOError(Errors.E052.format(path=data_path))
--> 649     return load_model_from_path(
    650         data_path,
    651         vocab=vocab,

~\anaconda3\lib\site-packages\spacy\util.py in load_model_from_path(model_path, meta, vocab, disable, enable, exclude, config)
    504     overrides = dict_to_dot(config)
    505     config = load_config(config_path, overrides=overrides)
--> 506     nlp = load_model_from_config(
    507         config,
    508         vocab=vocab,

~\anaconda3\lib\site-packages\spacy\util.py in load_model_from_config(config, meta, vocab, disable, enable, exclude, auto_fill, validate)
    552     # registry, including custom subclasses provided via entry points
    553     lang_cls = get_lang_class(nlp_config["lang"])
--> 554     nlp = lang_cls.from_config(
    555         config,
    556         vocab=vocab,

~\anaconda3\lib\site-packages\spacy\language.py in from_config(cls, config, vocab, disable, enable, exclude, meta, auto_fill, validate)
   1816                     # The pipe name (key in the config) here is the unique name
   1817                     # of the component, not necessarily the factory
-> 1818                     nlp.add_pipe(
   1819                         factory,
   1820                         name=pipe_name,

~\anaconda3\lib\site-packages\spacy\language.py in add_pipe(self, factory_name, name, before, after, first, last, source, config, raw_config, validate)
    799                     lang_code=self.lang,
    800                 )
--> 801             pipe_component = self.create_pipe(
    802                 factory_name,
    803                 name=name,

~\anaconda3\lib\site-packages\spacy\language.py in create_pipe(self, factory_name, name, config, raw_config, validate)
    659                 lang_code=self.lang,
    660             )
--> 661             raise ValueError(err)
    662         pipe_meta = self.get_factory_meta(factory_name)
    663         # This is unideal, but the alternative would mean you always need to

ValueError: [E002] Can't find factory for 'compound_splitter' for language Japanese (ja). This usually happens when spaCy calls `nlp.create_pipe` with a custom component name that's not registered on the current language class. If you're using a Transformer, make sure to install 'spacy-transformers'. If you're using a custom component, make sure you've added the decorator `@Language.component` (for function components) or `@Language.factory` (for class components).

Available factories: attribute_ruler, tok2vec, merge_noun_chunks, merge_entities, merge_subtokens, token_splitter, doc_cleaner, parser, beam_parser, lemmatizer, trainable_lemmatizer, entity_linker, ner, beam_ner, entity_ruler, tagger, morphologizer, senter, sentencizer, textcat, spancat, future_entity_ruler, span_ruler, textcat_multilabel, ja.morphologizer

該当のソースコード

pip install -U ginza
pip install -U ginza ja-ginza
pip install -U spacy
pip install transformers -U

import spacy 
nlp = spacy.load("ja_ginza")

試したこと

pip install -U ginza ja-ginza-electricaの実行
pip install -U ginza ja-ginzaの実行
pip install transformers -Uの実行

補足情報（FW/ツールのバージョンなど）

Windows10
Mecab　64bit
Python (jupyter notebook(anaconda))
です。