Abstract: A mechanism is provided, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for providing confidence rankings based on temporal semantics. Responsive to receiving an input question, a set of candidate answers is identified from a knowledge domain based on a correlation between an identified one or more predicates and an identified one or more arguments to the knowledge domain. A confidence score is associated with each of the candidate answers and each confidence score associated with each candidate answer is refined based on a set of temporal characteristics identified in the input question. A set of temporally refined candidate answers is then provided to the user.

Abstract: A digital work of literature is vocalized using enhanced text-to-speech (TTS) controls by analyzing a digital work of literature using natural language processing to identify speaking character voice characteristics associated with context of each quote as extracted from the first work of literature; converting the character voice characteristics to audio metadata to control text-to-speech audio synthesis for each quote; transforming the audio metadata into text-to-speech engine commands, each quote being associated with audio synthesis control parameters for the TTS in the context of each the quotes in the work of literature; and inputting the commands to a text-to-speech engine to cause vocalization of the work of literature according to the words of each quote, character voice characteristics of corresponding to each quote, and context corresponding to each quote.

Abstract: A digital work of literature is vocalized using enhanced text-to-speech (TTS) controls by analyzing a digital work of literature using natural language processing to identify speaking character voice characteristics associated with context of each quote as extracted from the first work of literature; converting the character voice characteristics to audio metadata to control text-to-speech audio synthesis for each quote; transforming the audio metadata into text-to-speech engine commands, each quote being associated with audio synthesis control parameters for the TTS in the context of each the quotes in the work of literature; and inputting the commands to a text-to-speech engine to cause vocalization of the work of literature according to the words of each quote, character voice characteristics of corresponding to each quote, and context corresponding to each quote.

Abstract: Mechanisms for ingesting a document from a corpus of documents for use by a Question and Answer (QA) system are provided. The mechanisms receive a document from a corpus of documents and generate one or more titles for the document based on an analysis of content of the document. The mechanisms generate score values for the titles based on a measure of a degree to which the titles represent the content of the document. The mechanisms store the score values in association with the titles as document metadata associated with the document and output the document and document metadata to the QA system. The QA system utilizes the document metadata and document to generate a candidate answer to an input question.

Abstract: Mechanisms for automatically generating a set of test questions for use in generating a test to be administered to human test takers are provided. The mechanisms ingest a document from a corpus of documents to select a potential test question answer from the document and generate a candidate test question based on the potential test question answer. The mechanisms evaluate the candidate test question using a Question and Answer (QA) system to generate a result indicative of whether the candidate test question should be maintained for test generation. The mechanisms store the candidate test question in the set of test questions in response to a result indicating that the candidate test question should be maintained for test generation.

Abstract: Mechanisms are provided for performing an analysis of content based on a flow of property between entities. The mechanisms analyze a corpus of unstructured documents to identify one or more asset transfer flow relationships between entities. The mechanisms generate an asset transfer flow model defining a flow of an asset between entities based on the one or more asset transfer flow relationships between entities. The mechanisms input the asset transfer flow model into an analysis engine for use in analyzing content. The mechanisms analyze the content using the asset transfer flow model to generate results of the analysis and output the results of the analysis based on the asset transfer flow model.

Abstract: A table structure corresponding to the table is selected to describe when cells in a cell-pair in the table structure should be similar to one another. A cell similarity function is selected to compare the cells in the cell-pair and output a probability that the cell-pair includes cells that contain values that are similar to one another according to a criteria. A cell similarity probability is determined of a first cell and a second cell in a first cell-pair in the table structure being similar to each other according to the cell similarity function. A computed probability is adjusted of the table structure representing the table using the cell similarity probability. The computed probability is indicated as a probability of a first model representing the table, wherein the first model is a function of the table structure and the selected cell similarity function.

Abstract: A table structure corresponding to the table is selected to describe when cells in a cell-pair in the table structure should be similar to one another. A cell similarity function is selected to compare the cells in the cell-pair and output a probability that the cell-pair includes cells that contain values that are similar to one another according to a criteria. A cell similarity probability is determined of a first cell and a second cell in a first cell-pair in the table structure being similar to each other according to the cell similarity function. A computed probability is adjusted of the table structure representing the table using the cell similarity probability. The computed probability is indicated as a probability of a first model representing the table, wherein the first model is a function of the table structure and the selected cell similarity function.

Abstract: A system, and computer program product for augmenting business process execution using natural language processing are provided in the illustrative embodiments Information related to a state in a business process is extracted from the business process executing in a data processing system. A set of natural language (NL) questions is formed based on the information and a transition from the state defined in the business process. The set of NL questions is answered with a corresponding set of NL answers, an NL answer in the set of NL answers having an associated confidence rating. A determination is made whether a confidence rating in the set of NL answers exceeds a threshold level of confidence. In response to the confidence rating exceeding the threshold, a task is executed to perform the transition in the business process.

Abstract: A method for augmenting business process execution using natural language processing is provided in the illustrative embodiments Information related to a state in a business process is extracted from the business process executing in a data processing system. A set of natural language (NL) questions is formed based on the information and a transition from the state defined in the business process. The set of NL questions is answered with a corresponding set of NL answers, an NL answer in the set of NL answers having an associated confidence rating. A determination is made whether a confidence rating in the set of NL answers exceeds a threshold level of confidence. In response to the confidence rating exceeding the threshold, a task is executed to perform the transition in the business process.

Abstract: An approach is provided for an information handling system that includes a processor and a memory to generate a table of contents pertaining to a document. The approach semantically analyzes the document to identify semantic relationships of proximate elements of the document. A number of candidate headings corresponding to a semantically related section of the document are identified and each of the candidate headings are scored. Based on the scores of each of the candidate headings, a section heading for the semantically related section of the document is selected. The selected heading is then included in the table of contents for the section of the document. The process of identifying candidate headings, scoring candidates, and selecting the section heading is repeated for other semantically related sections of the document.

Abstract: A method, system, and computer program product for creating or augmenting a business process model using a question and answer (Q and A) system are provided in the illustrative embodiments. A request to create the business process model of a business process is received. A knowledgebase is created using a business process modeling (BPM) data and user domain data. the user domain data comprises a combination of unstructured documents and structured documents related to an operation in a user domain. A natural language (NL) question is formed corresponding to the request. The NL question and the knowledgebase are submitted to the Q and A system. A set of answers is received from the Q and A system responsive to the NL question. An answer is presented as a part of the business process model.

Abstract: Mechanisms are provided for performing tabular data correction in a document. The mechanisms receive a natural language document comprising a portion of content and analyze the portion of content within the natural language document to identify an erroneous sub-portion comprising an erroneous or missing item of information. The mechanisms generate a semantic signature for the erroneous sub-portion and generate a query based on the semantic signature. The mechanisms apply the query to a knowledge base to identify a candidate sub-portion of content. The mechanisms correct the erroneous sub-portion using the identified candidate sub-portion of content to generate a corrected natural language document.

Abstract: An approach is provided for an information handling system to present knowledge-based information. In the approach, a semantic analysis is performed on the document with the analysis resulting in various sets of semantic content. Each of the sets of semantic content corresponds to an area in the document. The areas of the document are visually highlighted using visual indicators that show the availability of the sets of semantic content to a user via a user interface. In response to a user selection, such as a selection using the user interface or a user specified configuration setting, a selected set of semantic content is displayed to the user using the interface.

Abstract: Mechanisms are provided for generating a lexical resource for linguistic analysis. A document data structure is received that comprises a renaming directive and filter logic is applied to the document data structure to identify the renaming directive within the document data structure. The renaming directive is analyzed to identify a relationship between semantic concepts represented by the renaming directive that are to be used to update a lexical resource based on the renaming directive. The lexical resource is updated based on results of analyzing the renaming directive. The updated lexical resource is output to a linguistic analysis system which performs linguistic analysis of a portion of textual content based on the updated lexical resource.

Abstract: An approach is provided for an information handling system to present knowledge-based information. In the approach, a semantic analysis is performed on the document with the analysis resulting in various sets of semantic content. Each of the sets of semantic content corresponds to an area in the document. The areas of the document are visually highlighted using visual indicators that show the availability of the sets of semantic content to a user via a user interface. In response to a user selection, such as a selection using the user interface or a user specified configuration setting, a selected set of semantic content is displayed to the user using the interface.

Abstract: Mechanisms are provided for performing tabular data correction in a document. Tabular data is received and analyzed to identify at least one portion of the tabular data having an erroneous/missing data value. A functional dependency of the at least one portion of the tabular data on one or more other portions of the tabular data is determined. A correct data value for the erroneous or missing data value of the at least one portion of the tabular data is determined based on the functional dependency of the at least one portion. In addition, the tabular data is modified to replace the erroneous or missing data value with the correct data value and thereby generate a modified table data. A processing operation is then performed on the modified table data to generate a resulting output.

Abstract: A system, and computer program product for subject-matter analysis of tabular data are provided in the illustrative embodiments. A first document including the tabular data is received. A library of functional signatures for a first subject-matter domain is selected. A determination is made whether a threshold number of functional signatures from the selected library are applicable to the tabular data, wherein a functional signature is applicable to the tabular data when values in the tabular data correspond to an operation and a table structure specified in the functional signature. Responsive to the threshold number of functional signatures from the selected library being applicable to the tabular data, a processor and a memory process the first document according to a process for the first subject matter domain selected from a plurality of processes for respective subject matter domains.

Abstract: A method for subject-matter analysis of tabular data is provided in the illustrative embodiments. A first document including the tabular data is received. A library of functional signatures for a first subject-matter domain is selected. A determination is made whether a threshold number of functional signatures from the selected library are applicable to the tabular data, wherein a functional signature is applicable to the tabular data when values in the tabular data correspond to an operation and a table structure specified in the functional signature. Responsive to the threshold number of functional signatures from the selected library being applicable to the tabular data, a processor and a memory process the first document according to a process for the first subject matter domain selected from a plurality of processes for respective subject matter domains.

Abstract: A system, and computer program product for discovering relationships in tabular data are provided in the illustrative embodiments. A set of documents is received, a document in the set including the tabular data. A cell in the tabular data is selected whose dependencies are to be determined. A hypothesis to use in conjunction with the cell is selected. Whether the hypothesis applies to a selected portion of the document is tested by determining whether a conclusion in the hypothesis can be computed using a function specified in the hypothesis on the selected portion. The selected portion can be a selected cell-range in the tabular data or content in a non-tabular portion of the document. The hypothesis is utilized to describe the cell relative to the selected portion.