Abstract: A mechanism is provided for optimizing parsing of grammatical prose in a multi-prose electronic document. A received multi-prose electronic document is partitioned into a set of text segments of homogenous prose. A set of predefined Natural Language (NL) parsers is executed on each text segment in order to discern and measure a quality of parses by each NL parser throughout the multi-prose electronic document. A cross-parse analysis of the multi-prose electronic document and an aggregation of adjacent clauses or sentences of poor quality parses are performed. For each text segment, aggregation patterns yielding a best semantic role match are identified from one of the set of predefined NL parsers. Then, a parsed electronic document is generated using the set of predefined NL parsers such that each text segment is parsed by a NL parser that has the best semantic role match to that text segment.

Abstract: A mechanism is provided for semantic graph augmentation for domain adaptation. A semantic graph is provided based on a knowledge base in which concepts are linked by semantic relationships. A domain corpus of content in a new target domain is analyzed for adaptation with reference to one or more resources that provide syntactic analysis of the domain content that links portions of the domain corpus to existing concepts and links in the semantic graph. Triples are extracted from the analysis of the domain corpus of any two concepts that share a linking syntactic relationship. The triples are evaluated as potential relationship assertions. A relationship assertion is selected for addition as a new link between existing concepts in the semantic graph.

Abstract: This illustrative embodiments provide a mechanism for correcting a phonetically sourced spelling mistake. The mechanism receives a language text string comprising at least one spelling mistake word and transcribes the at least one spelling mistake word into a phonetic form of the spelling mistake word using a phonetic dictionary. The mechanism locates a correctly spelled phonetic form from a phonetic form dictionary having shortest edit distance between characters of the correctly spelled phonetic form word and the phonetic transcription whereby the phonetic form dictionary comprises correctly spelled words and associated phonetic forms of the correctly spelled words. The mechanism substitutes the correctly spelled word for the spelling mistake word in the text string.

Abstract: This illustrative embodiments provide a mechanism for correcting a phonetically sourced spelling mistake. The mechanism receives a language text string comprising at least one spelling mistake word and transcribes the at least one spelling mistake word into a phonetic form of the spelling mistake word using a phonetic dictionary. The mechanism locates a correctly spelled phonetic form from a phonetic form dictionary having shortest edit distance between characters of the correctly spelled phonetic form word and the phonetic transcription whereby the phonetic form dictionary comprises correctly spelled words and associated phonetic forms of the correctly spelled words. The mechanism substitutes the correctly spelled word for the spelling mistake word in the text string.

Abstract: Mechanisms are provided for modifying an ontology for use with a natural language processing (NLP) task. A model of the ontology is obtained that comprises nodes representing concepts of the ontology and edges between nodes representing relationships between associated nodes of the ontology. A spreading activation operation is performed on the model of the ontology with the spreading activation operation matching a portion of a textual source to a matching node of the model and identifying related nodes to the matching node through edges of the model associated with the matching node to thereby generate an activation network. The activation network is evaluated with regard to a chosen NLP task to determine a performance metric for the NLP task associated with the nodes of the model. Based on the results, one of the model or a configuration of the activation network may be modified.

Abstract: A mechanism is provided for optimizing parsing of grammatical prose in a multi-prose electronic document. A received multi-prose electronic document is partitioned into a set of text segments of homogenous prose. A set of predefined Natural Language (NL) parsers is executed on each text segment in order to discern and measure a quality of parses by each NL parser throughout the multi-prose electronic document. A cross-parse analysis of the multi-prose electronic document and an aggregation of adjacent clauses or sentences of poor quality parses are performed. For each text segment, aggregation patterns yielding a best semantic role match are identified from one of the set of predefined NL parsers. Then, a parsed electronic document is generated using the set of predefined NL parsers such that each text segment is parsed by a NL parser that has the best semantic role match to that text segment.

Abstract: Mechanisms are provided for modifying an ontology for use with a natural language processing (NLP) task. A model of the ontology is obtained that comprises nodes representing concepts of the ontology and edges between nodes representing relationships between associated nodes of the ontology. A spreading activation operation is performed on the model of the ontology with the spreading activation operation matching a portion of a textual source to a matching node of the model and identifying related nodes to the matching node through edges of the model associated with the matching node to thereby generate an activation network. The activation network is evaluated with regard to a chosen NLP task to determine a performance metric for the NLP task associated with the nodes of the model. Based on the results, one of the model or a configuration of the activation network may be modified.

Abstract: Mechanisms are provided for generating section metadata for an electronic document. These mechanisms receive a document and analyze the document to identify concepts present within textual content of the document. The mechanisms correlate concepts within the textual content with one another to identify concept groups based on the application of one or more rules defining related concepts or concept patterns. The mechanisms determine sections of text within the textual content based on the correlation of concepts within the textual content. Based on results of the determining, the mechanisms generate section metadata for the document and store the section metadata in association with the document for use by a document processing system.

Abstract: Mechanisms are provided for generating section metadata for an electronic document. These mechanisms receive a document and analyze the document to identify concepts present within textual content of the document. The mechanisms correlate concepts within the textual content with one another to identify concept groups based on the application of one or more rules defining related concepts or concept patterns. The mechanisms determine sections of text within the textual content based on the correlation of concepts within the textual content. Based on results of the determining, the mechanisms generate section metadata for the document and store the section metadata in association with the document for use by a document processing system.