Abstract: Systems, apparatuses, methods, and computer program products are disclosed for unsupervised named entity recognition. An example method includes receiving, by a communications circuitry, a reference named entity list, the reference named entity list identifying a set of named entities and an entity type of each identified named entity. The example method further includes generating, by a vectorizer, vectors from the named entities identified in the reference named entity list, and consolidating, by a synthesizer, the generated vectors into a set of representative vectors, wherein each representative vector is associated with a particular entity type. Finally, the example method receiving, by an analysis engine, a set of text, and performing, by the analysis engine, named entity recognition on the set of text using the set of representative vectors to generate a tagged set of text.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for automatically determining accuracy of entity recognition of text. An example method includes segmenting a service entity recognition analysis of the text and a gold entity recognition analysis of the text into common superstrings that define entity spans. The example method further includes classifying each of the entity spans based on an accuracy of entity recognition in the service analysis of the text corresponding to the entity spans using a classification system that differentiates accurately identified but improperly bounded entities into at least three subcategories to obtain an entity accuracy classification. The example method also includes obtaining a score report based on the entity accuracy classification. The example method additionally includes performing an action set based on the entity accuracy classification.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for automatically determining accuracy of entity recognition of text. An example method includes segmenting a service entity recognition analysis of the text and a gold entity recognition analysis of the text into common superstrings that define entity spans. The example method further includes classifying each of the entity spans based on an accuracy of entity recognition in the service analysis of the text corresponding to the entity spans using a classification system that differentiates accurately identified but improperly bounded entities into at least three subcategories to obtain an entity accuracy classification. The example method also includes obtaining a score report based on the entity accuracy classification. The example method additionally includes performing an action set based on the entity accuracy classification.