Repository: pykeen/pykeen
Issue: The example error in Docs/GETTING STARTED/Representations/Lable-based
Root cause: Documentation Deficiency

### Describe the bug

Can't import  EmbeddingSpecification
```python
from pykeen.pipeline import pipeline
from pykeen.datasets import get_dataset
from pykeen.nn.representation import EmbeddingSpecification, LabelBasedTransformerRepresentation
from pykeen.models import ERModel

dataset = get_dataset(dataset="nations")
entity_representations = LabelBasedTransformerRepresentation.from_triples_factory(
    triples_factory=dataset.training,
)
result = pipeline(
    dataset=dataset,
    model=ERModel,
    model_kwargs=dict(
        interaction="ermlpe",
        interaction_kwargs=dict(
            embedding_dim=entity_representations.embedding_dim,
        ),
        entity_representations=entity_representations,
        relation_representations=EmbeddingSpecification(
            shape=entity_representations.shape,
        ),
    ),
    training_kwargs=dict(
        num_epochs=1,
    ),
)
model = result.model
```

### How to reproduce

Run the example.

### Environment

| Key             | Value                    |
|-----------------|--------------------------|
| OS              | nt                       |
| Platform        | Windows                  |
| Release         | 10                       |
| Time            | Sat Jul 23 15:54:22 2022 |
| Python          | 3.7.12                   |
| PyKEEN          | 1.8.1                    |
| PyKEEN Hash     | UNHASHED                 |
| PyKEEN Branch   |                          |
| PyTorch         | 1.12.0+cu113             |
| CUDA Available? | true                     |
| CUDA Version    | 11.3                     |
| cuDNN Version   | 8302                     |


### Additional information

_No response_

### Issue Template Checks

- [X] This is not a feature request (use a different issue template if it is)
- [X] This is not a question (use the [discussions](https://github.com/pykeen/pykeen/discussions/new) forum instead)
- [X] I've read the text explaining why including environment information is important and understand if I omit this information that my issue will be dismissed

Hi @YBAgg ,

this error is already fixed on the `master` branch. You can also see at readthedocs by selecting "latest" instead of stable, i.e., https://pykeen.readthedocs.io/en/latest/tutorial/representations.html

It will be updated in the default view, once we make our next release.

> Hi @YBAgg ,
> 
> this error is already fixed on the `master` branch. You can also see at readthedocs by selecting "latest" instead of stable, i.e., https://pykeen.readthedocs.io/en/latest/tutorial/representations.html
> 
> It will be updated in the default view, once we make our next release.
Thanks a lot!!!
One more question，I need KG's embedding result for downstream tasks, but I did not find the example how to do that in docs,  it would be very helpful if you could give me the relevant  link.@mberr 


> > Hi @YBAgg ,
> > this error is already fixed on the `master` branch. You can also see at readthedocs by selecting "latest" instead of stable, i.e., https://pykeen.readthedocs.io/en/latest/tutorial/representations.html
> > It will be updated in the default view, once we make our next release.
> > Thanks a lot!!!
> > One more question，I need KG's embedding result for downstream tasks, but I did not find the example how to do that in docs,  it would be very helpful if you could give me the relevant  @mberr


Hi @mberr 
I have find how to get KG's embedding result in docs
[https://pykeen.readthedocs.io/en/stable/tutorial/first_steps.html?highlight=embedding#using-learned-embeddings](url)
But I still don't kown how to get specific entity's or relation's embedding result, can you give me a demonstration in the code below？Like get the embedding of "uk".

```python
from pykeen.nn.representation import LabelBasedTransformerRepresentation
from typing import List
import pykeen.nn
from pykeen.pipeline import pipeline
import torch`
result = pipeline(
    model='TransE',
    dataset='nations',
)
model = result.model

entity_representation_modules: List['pykeen.nn.Representation'] = model.entity_representations
relation_representation_modules: List['pykeen.nn.Representation'] = model.relation_representations

entity_embeddings: pykeen.nn.Embedding = entity_representation_modules[0]
relation_embeddings: pykeen.nn.Embedding = relation_representation_modules[0]

entity_embedding_tensor: torch.FloatTensor = entity_embeddings()
relation_embedding_tensor: torch.FloatTensor = relation_embeddings()
```

You need to get the (integer) IDs for the given label. You can find examples on the section just above the one you linked ( https://pykeen.readthedocs.io/en/stable/tutorial/first_steps.html?highlight=embedding#mapping-entity-and-relation-identifiers-to-their-names ).

e.g.:
```python
ids = torch.as_tensor(triples_factory.entities_to_ids(["china", "egypt"]))
entity_embeddings = entity_representation_modules[0]
x = entity_embeddings(ids)
```

Closing this as the issues seem to be originating from a very old version of pykeen and the answers are already in the docs