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notebooks/search/09-semantic-text.ipynb

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"The `inference_id` parameter defines the inference endpoint that is used to generate the embeddings for the field.\n",
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"Then we configured the `plot` field to [copy its value](https://www.elastic.co/guide/en/elasticsearch/reference/current/copy-to.html) to the `plot_semantic` field.\n",
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"While the use of `copy_to` is not required to leverage semantic search it does enable use cases like hybrid search where semantic and lexical techniques are used together. The contents of the `plot` field are copied into the `plot_semantic` field which enables searches over both fields at once."
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"While `copy_to` is not required to use `semantic_text`, it enables use cases like hybrid search where semantic and lexical techniques are used together. We will cover a hybrid search example later in this notebook."
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"These results demonstrate that the application of lexical search techniques can help focus the results, while retaining many of the advantages of semantic search.\n",
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"In this example, the top search results are all still movies involving organized crime, but the `multi_match` query keeps the long tail shorter and focused on movies in the crime genre.\n",
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"\n",
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"Notice how we specify the `plot` field in the multi_match query. The content of this field is also contained in the semantic field `plot_semantic` due to the use of `copy_to` this allows the boolean query to consider both lexical and semantic similarity of the `plot` field.\n",
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"The `copy_to` parameter we defined in the mapping enables this query pattern. It ensures that the content provided for the `plot` field is indexed both lexically and semantically.\n",
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"Note the `boost` parameters applied to the `multi_match` and `semantic` queries.\n",
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"Combining lexical and semantic search techniques in a boolean query like this is called \"linear combination\" and when doing this, it is important to normalize the scores of the component queries.\n",

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