### 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
topScoresCollector.accept(toReturn);
            return;
        }
        for (int i = seq2Start; i < tokenSize; i++) {
            for (int j = i; j < (maxAnswerLength + i) && j < tokenSize; j++) {
                topScoresCollector.accept(
                    new ScoreAndIndices(i - seq2Start, j - seq2Start, startNormalized[i] * endNormalized[j], spanIndex)
                );
            }
        }
    }
    static double[] normalizeWith(double[] values, IntPredicate mutateIndex, double predicateValue) {
        double[] toReturn = new double[values.length];
        for (int i = 0; i < values.length; i++) {
            toReturn[i] = values[i];
            if (mutateIndex.test(i) == false) {
                toReturn[i] = predicateValue;
            }
        }
        double expSum = 0.0;
        for (double v : toReturn) {
            expSum += Math.exp(v);
        }
        double diff = Math.log(expSum);
        for (int i = 0; i < toReturn.length; i++) {
            toReturn[i] = Math.exp(toReturn[i] - diff);
        }
        return toReturn;
    }
    static class ScoreAndIndicesPriorityQueue extends PriorityQueue<ScoreAndIndices> {