Geneea NLP platform integration with Keboola Connection

Integration of the Geneea API with Keboola Connection.

This is a Docker container used for running general-purpose NLP analysis jobs in the KBC. Automatically built Docker images are available at Docker Hub Registry.

The supported NLP analysis types are: sentiment, entities, tags, relations.

Building a container

To build this container manually one can use:

git clone https://github.com/Geneea/keboola-nlp-analysis.git
cd keboola-nlp-analysis
sudo docker build --no-cache -t geneea/keboola-nlp-analysis .

Running a container

This container can be run from the Registry using:

sudo docker run \
--volume=/home/ec2-user/data:/data \
--rm \
geneea/keboola-nlp-analysis:latest

Note: --volume needs to be adjusted accordingly.

Sample configuration

Mapped to /data/config.json

{
  "storage": {
    "input": {
      "tables": [
        {
          "destination": "source.csv"
        }
      ]
    }
  },
  "parameters": {
    "user_key": "<ENTER API KEY HERE>",
    "columns": {
      "id": ["date", "subject"],
      "title": ["subject"],
      "text": ["body_1", "body_2"]
    },
    "analysis_types": ["sentiment", "entities", "tags", "relations"],
    "language": "cs",
    "domain": "news",
    "correction": "basic",
    "diacritization": "auto",
    "use_beta": false
  }
}

Output format

The results of the NLP analysis are written into four tables.

• analysis-result-documents.csv with document-level results in the following columns:

  • all id columns from the input table (used as primary keys)
  • language detected language of the document, as ISO 639-1 language code
  • sentimentValue detected sentiment of the document, from an interval [-1.0; 1.0]
  • sentimentPolarity detected sentiment of the document (-1, 0 or 1)
  • sentimentLabel sentiment of the document as a label (negative, neutral or positive)
  • sentimentDetailedLabel sentiment of the document as a detailed label
  • usedChars the number of characters used by this document

• analysis-result-sentences.csv with sentence-level results has the following columns:

  • all id columns from the input table (used as primary keys)
  • index zero-based index of the sentence in the document, (primary key)
  • segment text segment where the sentence is located
  • text the sentence text
  • sentimentValue detected sentiment of the sentence, from an interval [-1.0; 1.0]
  • sentimentPolarity detected sentiment of the sentence (-1, 0 or 1)
  • sentimentLabel sentiment of the sentence as a label (negative, neutral or positive)
  • sentimentDetailedLabel sentiment of the sentence as a detailed label

  There are multiple rows per one document. All id columns plus the index column are part of the primary key.

• analysis-result-entities.csv with entity-level results has the following columns:

  • all id columns from the input table (used as primary keys)
  • type type of the found entity, e.g. person, organization or tag, (primary key)
  • text disambiguated and standardized form of the entity, e.g. John Smith, Keboola, safe carseat, (primary key)
  • score relevance score of the entity, e.g. 0.8
  • entityUid unique ID of the entity, may be empty
  • sentimentValue detected sentiment of the entity, from an interval [-1.0; 1.0]
  • sentimentPolarity detected sentiment of the entity (-1, 0 or 1)
  • sentimentLabel sentiment of the entity as a label (negative, neutral or positive)
  • sentimentDetailedLabel sentiment of the entity as a detailed label

  There are multiple rows per one document. All id columns plus type and text columns are part of the primary key.

  Note that the table also contains topic tags, marked as tag in the type column.

• analysis-result-relations.csv with relation-level results has the following columns:

  • all id columns from the input table (used as primary keys)
  • type type of the found relation, VERB or ATTR, (primary key)
  • name textual name of the relation, e.g. buy or smart, (primary key)
  • negated negation flag of the relation, true or false, (primary key)
  • subject possible subject of the relation (primary key)
  • object possible object of the relation (primary key)
  • subjectType type of the relation's subject
  • objectType type of the relation's object
  • subjectUid unique ID of the relation's subject
  • objectUid unique ID of the relation's object
  • sentimentValue detected sentiment of the relation, from an interval [-1.0; 1.0]
  • sentimentPolarity detected sentiment of the relation (-1, 0 or 1)
  • sentimentLabel sentiment of the relation as a label (negative, neutral or positive)
  • sentimentDetailedLabel sentiment of the relation as a detailed label

  There are multiple rows per one document. All id columns plus type, name, negated, subject, object columns are part of the primary key.