### Elasticsearch Version

8.9.0

### Installed Plugins

_No response_

### Java Version

_bundled_

### OS Version

any

### Problem Description

If the context text supplied to the Question Answering task is longer than the model's `max_sequence_length` and `truncate` is set to `none` then inference on the model fails with the message:

```
status_exception: question answering result has invalid dimension, expected 2 found [6] 
```
<img width="1438" alt="Screenshot 2023-07-25 at 08 21 37" src="https://github.com/elastic/elasticsearch/assets/2353640/12d296f6-03b2-4cda-89ce-7399348c4104">


### Steps to Reproduce

Use long input text to the question answering task


### Work Aroundf
The fix is to truncate the context which unfortunately may remove the part of the document containing the answer. For reference the call is documented here

```
POST _ml/trained_models/distilbert-base-cased-distilled-squad/deployment/_infer
{
  "docs":[{ "text_field": "question answering context"}],
  "inference_config": {
    "question_answering": {
      "question": "The question to ask",
      "tokenization": {
        "bert": {
          "truncate": "second",
          "span": -1          
        }
      }
    }
  }
}
````

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/inference/nlp/QuestionAnsweringProcessor.java
throw new ElasticsearchStatusException(
                    "question answering result has invalid dimensions; start positions [{}] must equal potential end [{}]",
                    RestStatus.INTERNAL_SERVER_ERROR,
                    starts.length,
                    ends.length
                );
            }
            List<TokenizationResult.Tokens> tokensList = tokenization.getTokensBySequenceId().get(0);
            if (starts.length != tokensList.size()) {
                throw new ElasticsearchStatusException(
                    "question answering result has invalid dimensions; start positions number [{}] equal batched token size [{}]",
                    RestStatus.INTERNAL_SERVER_ERROR,
                    starts.length,
                    tokensList.size()
                );
            }
            final int numAnswersToGather = Math.max(numTopClasses, 1);
            ScoreAndIndicesPriorityQueue finalEntries = new ScoreAndIndicesPriorityQueue(numAnswersToGather);
            for (int i = 0; i < starts.length; i++) {
                topScores(
                    starts[i],
                    ends[i],
                    numAnswersToGather,
                    finalEntries::insertWithOverflow,
                    tokensList.get(i).seqPairOffset(),
                    tokensList.get(i).tokenIds().length,
                    maxAnswerLength,
                    i
                );
            }