Top-level aggregation representation.
Top-level aggregation representation.
the name of the aggregation.
a list of models.Bucket representing the distinct aggregated result values.
Abstract representation for the bucketing aggregation.
Document representation.
Document representation.
unique document identifier.
document body containing raw text.
creation date and time of the document.
document content enriched with tags ( [...] ) for highlighting. This field is used to highlight full-text search results.
Representation for an entity.
Representation for an entity.
unique id and primary key of the entity.
the entity name.
the entity type e.g. Person, Organisation, Location or Miscellaneous.
the document occurrence i.e. in how many documents does this entity occur.
Representation for a search query to find the most relevant documents.
Representation for a search query to find the most relevant documents.
match documents that contain the given expression in the document body.
a map linking from document metadata keys to a list of instances for this metadata. Different metadata keys are joined via a logical and, whereas different instances of the same metadata key are joined via a logical or.
a list of entity ids that should occur in the document.
start date for the document creation date (inclusive).
end date for the document creation date (inclusive).
start date for the time expression mentioned in the document body (inclusive).
end date for the time expresson mentioned in the document body (inclusive).
Representation for an entity occurrence within the body of a document.
Representation for an entity occurrence within the body of a document.
the offset start of the entity occurrence.
the offset end of the entity occurrence.
Storage representation for the document iterator.
Storage representation for the document iterator.
This representation is used to store the current document iterator matching a search query between different user requests.
the number of documents matching the search query.
the document iterator consisting of documents matching the search query.
the hash code of the search query i.e. models.Facets#hashCode.
For usage see controllers.DocumentController.
Representation for important terms including their importance value.
Representation for important terms including their importance value.
the important term value.
the score of the important term. Higher values represent more important terms.
Aggregated result representation for generic metadata such as "Sender_name" or "Classification_level".
Aggregated result representation for generic metadata such as "Sender_name" or "Classification_level".
the name of the aggregated value.
the number of times this instance occurs in the background collection.
Representation for a co-occurrence network.
Representation for a co-occurrence network.
the vertices of the network.
the edges of the network.
Aggregated result representation for entities.
Aggregated result representation for entities.
the id of the entity.
the number of times the entity occurs in the background collection.
Representation for a relationship.
Representation for a relationship.
the first adjacent node.
the second adjacent node.
the document occurrence i.e. in how many documents does this relationship occur.
Representation for a document tag.
Representation for a document tag.
the unique tag id.
the unique document id.
the corresponding tag label.
Companion object for models.Document instances.
Companion object for models.Entity instances.
Companion object for models.Facets.
Companion object for models.KeyTerm instances.
Level of detail for the models.services.TimelineService.
Companion object for models.Relationship instances.
Companion object for models.Tag instances.
Provides classes for accessing the underlying data.
Provides classes for dealing with the backend services.