Detect Food in Text

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Detect Food in Text

Take any text and find all mentions of food contained within it. This task is also called Named Entity Recognition (NER). In this case, the entities are foods. Either dishes, such as pizza or cheeseburger, or ingredients, such as cucumber or almonds.

Options

Content Type (*)
The content type.
Body
Result Format

Specify how the response should be mapped to the table output. The following formats are available:

Raw Response: Returns the raw response in a single row with the following columns:

  • body: Response body
  • status: HTTP status code

Input Ports

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Configuration data.

Output Ports

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Result of the request depending on the selected Result Format.
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Configuration data (this is the same as the input port; it is provided as passthrough for sequentially chaining nodes to declutter your workflow connections).

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Installation

To use this node in KNIME, install the extension spoonacular Nodes from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: NodePit
Plugin version: 1.2.1.202407040739
On NodePit since: 2024-07-09
Last update: 2024-11-21
KNIME versions: Since v4.4
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