def field_schema(
    field: ModelField,
    *,
    by_alias: bool = True,
    model_name_map: Dict[TypeModelOrEnum, str],
    ref_prefix: Optional[str] = None,
    ref_template: str = default_ref_template,
    known_models: Optional[TypeModelSet] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any], Set[str]]:
    """
    Process a Pydantic field and return a tuple with a JSON Schema for it as the first item.
    Also return a dictionary of definitions with models as keys and their schemas as values. If the passed field
    is a model and has sub-models, and those sub-models don't have overrides (as ``title``, ``default``, etc), they
    will be included in the definitions and referenced in the schema instead of included recursively.

    :param field: a Pydantic ``ModelField``
    :param by_alias: use the defined alias (if any) in the returned schema
    :param model_name_map: used to generate the JSON Schema references to other models included in the definitions
    :param ref_prefix: the JSON Pointer prefix to use for references to other schemas, if None, the default of
      #/definitions/ will be used
    :param ref_template: Use a ``string.format()`` template for ``$ref`` instead of a prefix. This can be useful for
      references that cannot be represented by ``ref_prefix`` such as a definition stored in another file. For a
      sibling json file in a ``/schemas`` directory use ``"/schemas/${model}.json#"``.
    :param known_models: used to solve circular references
    :return: tuple of the schema for this field and additional definitions
    """
    s, schema_overrides = get_field_info_schema(field)

    validation_schema = get_field_schema_validations(field)
    if validation_schema:
        s.update(validation_schema)
        schema_overrides = True

    f_schema, f_definitions, f_nested_models = field_type_schema(
        field,
        by_alias=by_alias,
        model_name_map=model_name_map,
        schema_overrides=schema_overrides,
        ref_prefix=ref_prefix,
        ref_template=ref_template,
        known_models=known_models or set(),
    )

    # $ref will only be returned when there are no schema_overrides
    if '$ref' in f_schema:
        return f_schema, f_definitions, f_nested_models
    else:
        s.update(f_schema)
        return s, f_definitions, f_nested_models

    Process a Pydantic field and return a tuple with a JSON Schema for it as the first item.
    Also return a dictionary of definitions with models as keys and their schemas as values. If the passed field
    is a model and has sub-models, and those sub-models don't have overrides (as ``title``, ``default``, etc), they
    will be included in the definitions and referenced in the schema instead of included recursively.

    :param field: a Pydantic ``ModelField``
    :param by_alias: use the defined alias (if any) in the returned schema
    :param model_name_map: used to generate the JSON Schema references to other models included in the definitions
    :param ref_prefix: the JSON Pointer prefix to use for references to other schemas, if None, the default of
      #/definitions/ will be used
    :param ref_template: Use a ``string.format()`` template for ``$ref`` instead of a prefix. This can be useful for
      references that cannot be represented by ``ref_prefix`` such as a definition stored in another file. For a
      sibling json file in a ``/schemas`` directory use ``"/schemas/${model}.json#"``.
    :param known_models: used to solve circular references
    :return: tuple of the schema for this field and additional definitions
    
pydantic/v1/schema.py