Abstract: Automatic information extraction apparatus for extracting data for review by a human curator from digital representations of documents comprising natural language text, the automatic information extraction apparatus having a plurality of selectable operating modes in which the automatic information extraction apparatus is operable to extract different data for review by a human curator. In the different operating modes, the information extraction apparatus may extract data with a different balance between recall and precision.

Abstract: Automatic information extraction apparatus for extracting data for review by a human curator from digital representations of documents comprising natural language text, the automatic information extraction apparatus having a plurality of selectable operating modes in which the automatic information extraction apparatus is operable to extract different data for review by a human curator. In the different operating modes, the information extraction apparatus may extract data with a different balance between recall and precision.

Abstract: There is disclosed a method of recognising named entities in a text-containing document, represented by text document data. The received text document data comprising a plurality of tokens, one or more of the said plurality of tokens being part of a plurality of entities. The text document data is analysed using one or more tagging modules which are operable to determine token label data in respect of at least the tokens which are part of a plurality of entities, wherein the token label data output by the one or more tagging modules comprises data representative of the location of the token within each of a plurality of entities. The token label data representative of the location of the token within each of a plurality of entities is used to determine the beginning and end of the entities which have been identified in the text document data.