Semantic search inner_hits

Versions v 3.1.0

When I run pure semantic search with dense vectors via neural query and with nested documents, the inner_hits only contain one result.

Example:

GET my_index/_search
{
  "query": {
    "nested": {
      "path": "embeddings",
      "query": {
        "neural": {
          "embeddings.embedding": {
            "query_text": "What is foo bar baz?",
            "model_id": "model_id",
            "k": 5
          }
        }
      },
      "inner_hits": {
        "size": 5,
        "_source": [
          "embeddings.text"
        ]
      }
    }
  }
}

The inner_hits will only contain 1 chunk per document, not respecting the size parameter.

When I however run this with hybrid search, the size parameter of inner_hit is respected:

GET my_index/_search?search_pipeline=minmax-pipeline
{
  "query": {
    "hybrid": {
      "queries": [
        {
          "nested": {
            "path": "embeddings",
            "query": {
              "match": {
                "embeddings.text": {
                  "query": "What is foo bar baz?"
                }
              }
            },
            "inner_hits": {
              "size": 5,
              "_source": [
                "embeddings.text"
              ]
            }
          }
        },
        {
          "nested": {
            "path": "embeddings",
            "query": {
              "neural": {
                "embeddings.embedding": {
                  "query_text": "What is foo bar baz?",
                  "model_id": "model_id",
                  "k": 5
                }
              }
            }
          }
        }
      ]
    }
  }
}

Is there a way to get more inner_hits result from the semantic search?

I am running into a scenario now where there are multiple chunks in the first parent document, which have better scores than the winning chunk in second parent document. Which means I am losing context.

And just as I ask the question, I find the "expand_nested_docs": true in the docs