Classic tokenizer

The classic tokenizer is a grammar based tokenizer that is good for English language documents. This tokenizer has heuristics for special treatment of acronyms, company names, email addresses, and internet host names. However, these rules don’t always work, and the tokenizer doesn’t work well for most languages other than English:

It splits words at most punctuation characters, removing punctuation. However, a dot that’s not followed by whitespace is considered part of a token.
It splits words at hyphens, unless there’s a number in the token, in which case the whole token is interpreted as a product number and is not split.
It recognizes email addresses and internet hostnames as one token.

Example output

edit

resp = client.indices.analyze(
    tokenizer="classic",
    text="The 2 QUICK Brown-Foxes jumped over the lazy dog's bone.",
)
print(resp)

response = client.indices.analyze(
  body: {
    tokenizer: 'classic',
    text: "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone."
  }
)
puts response

const response = await client.indices.analyze({
  tokenizer: "classic",
  text: "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone.",
});
console.log(response);

POST _analyze
{
  "tokenizer": "classic",
  "text": "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone."
}

The above sentence would produce the following terms:

[ The, 2, QUICK, Brown, Foxes, jumped, over, the, lazy, dog's, bone ]

Configuration

edit

The classic tokenizer accepts the following parameters:

max_token_length

The maximum token length. If a token is seen that exceeds this length then it is split at max_token_length intervals. Defaults to 255.

Example configuration

edit

In this example, we configure the classic tokenizer to have a max_token_length of 5 (for demonstration purposes):

resp = client.indices.create(
    index="my-index-000001",
    settings={
        "analysis": {
            "analyzer": {
                "my_analyzer": {
                    "tokenizer": "my_tokenizer"
                }
            },
            "tokenizer": {
                "my_tokenizer": {
                    "type": "classic",
                    "max_token_length": 5
                }
            }
        }
    },
)
print(resp)

resp1 = client.indices.analyze(
    index="my-index-000001",
    analyzer="my_analyzer",
    text="The 2 QUICK Brown-Foxes jumped over the lazy dog's bone.",
)
print(resp1)

response = client.indices.create(
  index: 'my-index-000001',
  body: {
    settings: {
      analysis: {
        analyzer: {
          my_analyzer: {
            tokenizer: 'my_tokenizer'
          }
        },
        tokenizer: {
          my_tokenizer: {
            type: 'classic',
            max_token_length: 5
          }
        }
      }
    }
  }
)
puts response

response = client.indices.analyze(
  index: 'my-index-000001',
  body: {
    analyzer: 'my_analyzer',
    text: "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone."
  }
)
puts response

const response = await client.indices.create({
  index: "my-index-000001",
  settings: {
    analysis: {
      analyzer: {
        my_analyzer: {
          tokenizer: "my_tokenizer",
        },
      },
      tokenizer: {
        my_tokenizer: {
          type: "classic",
          max_token_length: 5,
        },
      },
    },
  },
});
console.log(response);

const response1 = await client.indices.analyze({
  index: "my-index-000001",
  analyzer: "my_analyzer",
  text: "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone.",
});
console.log(response1);

PUT my-index-000001
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "my_tokenizer"
        }
      },
      "tokenizer": {
        "my_tokenizer": {
          "type": "classic",
          "max_token_length": 5
        }
      }
    }
  }
}

POST my-index-000001/_analyze
{
  "analyzer": "my_analyzer",
  "text": "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone."
}

The above example produces the following terms:

[ The, 2, QUICK, Brown, Foxes, jumpe, d, over, the, lazy, dog's, bone ]

« Character group tokenizer Edge n-gram tokenizer »