Abstract: Validating belief states of an artificial intelligence system includes providing a question answering service; detecting a negative sentiment of a user to an answer transmitted to a device associated with the user; and responsive to detecting the negative sentiment, detecting that the answer relates to a topic on which there is controversy. Next, a new belief state is added to the question answering service based on the controversy, and an updated answer is transmitted to the device, wherein the updated answer is based on the new belief state.

Abstract: A technique for transforming questions for a question answering (QA) system includes clustering received questions by contextual accordance into a question set. A base lexical answer type (LAT) for the question set is determined. LATs of discordant questions in the question set are transformed to the base LAT. Answers for the questions in the question set are aggregated. The aggregated answers are then displayed.

Abstract: According to an embodiment of the present invention, a system filters a collection of application programming interfaces based on input data representing information of a document to be processed, and generates a pipeline of filtered application programming interfaces. Each filtered application programming interface is sequentially executed within the pipeline. The document may be processed through the pipeline and visualizations based on the processing of the document may be generated, allowing the pipeline to be refined to produce desired output data selected within the visualizations. Embodiments of the present invention further include a method and computer program product for generating a pipeline of filtered application programming interfaces in substantially the same manner described above.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for ranking inclusion and exclusion criteria based on problematic language. A computer receives criteria and identifies semantic entailment between two or more criteria. The computer further identifies inclusionary criteria that appear as exclusionary criteria and exclusionary criteria that is difficult to interpret. The computer additionally identifies criteria having hypothetical, time specific, or complex language. Based on the computer identifying inclusionary criteria that appears as exclusionary criteria, exclusionary criteria that is difficult to interpret, or criteria having hypothetical, time specific, or complex language, the computer ranks the subject criteria based on the identified problematic language and presents the ranked criteria.

Abstract: A method for providing a hierarchical question answering system for presenting structured answers to a query is provided. The method may include receiving a query for a question answering system. The method may further include generating first queries based on the query. The method may further include generating second queries based on the first queries. The method may further include clustering the query, the first queries, and the second queries to form a hierarchy of queries. The method may also include processing the hierarchy of queries to generate answers. The method may further include clustering the answers to form a hierarchy of answers. The method may also include ranking the hierarchy of answers. The method may also include aggregating the hierarchy of answers to generate an optimal answer. The method may further include presenting the hierarchy of queries, the hierarchy of answers, and the optimal answer.

Abstract: Candidate answers are generated by a question-answering system in response to a question from a user. One or more generated candidate answers are compared to previous question-answer sets. The previous question-answer sets are indexed and stored in a database which includes a knowledge graph on the previous questions-answer sets. A previous question-answer set is identified as correlating with a first generated candidate answers. The previous question-answer set is identified using relationships of the database. The first generated candidate answer is restructured using the question as a statement which is embedded with the first generated candidate answer. The restructured generated candidate answer which correlates with the previous question-answer set is supplemented with content from the previous question-answer set.

Abstract: A system and method to manage a community development asset. The system includes an asset polling agent, a nomenclature taxonomy dictionary, and an asset discovery service. The asset polling agent identifies a descriptive term associated with an asset under development. The nomenclature taxonomy dictionary stores a list of synonym terms related to the descriptive term associated with the asset under development. The asset discovery service identifies a reusable asset of a plurality of reusable assets for use with the asset under development based on at least one term, from a combination of the descriptive term and the list of synonym terms related to the descriptive term, extracted from social network data.

Abstract: According to an embodiment of the present invention, a system filters a collection of application programming interfaces based on input data representing information of a document to be processed, and generates a pipeline of filtered application programming interfaces. Each filtered application programming interface is sequentially executed within the pipeline. The document may be processed through the pipeline and visualizations based on the processing of the document may be generated, allowing the pipeline to be refined to produce desired output data selected within the visualizations. Embodiments of the present invention further include a method and computer program product for generating a pipeline of filtered application programming interfaces in substantially the same manner described above.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for answering compound questions. A computer receives a compound question and identifies one or more sub questions. The computer identifies natural language processing features of the compound questions and generates a logical representation of the compound question. The computer retrieves and ranks candidate answers to the one or more sub questions and evaluates them in the context of other sub questions, then provides final answers to the one or more sub questions.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for extracting natural language relations between entities. A computer receives a configuration for associating one or more natural language questions with one or more entities and identifies the one or more entities annotated within a document. The computer answers the natural language questions associated with the identified one or more entities based on context surrounding the identified one or more entities. The computer may further transmit the natural language questions associated with the identified one or more entities and the surrounding context to a question and answer service, then receive answers to the natural language questions from the question and answer service. The computer may further determine whether the received answers correctly describe the relation between the identified one or more entities and other entities within the extracted surrounding context.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for ranking inclusion and exclusion criteria based on problematic language. A computer receives criteria and identifies semantic entailment between two or more criteria. The computer further identifies inclusionary criteria that appear as exclusionary criteria and exclusionary criteria that is difficult to interpret. The computer additionally identifies criteria having hypothetical, time specific, or complex language. Based on the computer identifying inclusionary criteria that appears as exclusionary criteria, exclusionary criteria that is difficult to interpret, or criteria having hypothetical, time specific, or complex language, the computer ranks the subject criteria based on the identified problematic language and presents the ranked criteria.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for identifying information gaps in corpora. A computer receives a document and extracts keywords from the document while filtering trivial keywords. The computer identifies and extracts top keywords detailed by the document using a topic modelling approach before determining whether the extracted top keywords exceed a threshold use frequency. Based on determining that the top keywords exceed a threshold use frequency, determining whether the top keywords have a relation to other entities within the document and, if so, determining whether the top keywords are defined within the document. Based on determining that the top keywords are not defined in the document, adding the top keywords to a list and defining the top keywords.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for extracting natural language relations between entities. A computer receives a configuration for associating one or more natural language questions with one or more entities and identifies the one or more entities annotated within a document. The computer answers the natural language questions associated with the identified one or more entities based on context surrounding the identified one or more entities. The computer may further transmit the natural language questions associated with the identified one or more entities and the surrounding context to a question and answer service, then receive answers to the natural language questions from the question and answer service. The computer may further determine whether the received answers correctly describe the relation between the identified one or more entities and other entities within the extracted surrounding context.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for extracting natural language relations between entities. A computer receives a configuration for associating one or more natural language questions with one or more entities and identifies the one or more entities annotated within a document. The computer answers the natural language questions associated with the identified one or more entities based on context surrounding the identified one or more entities. The computer may further transmit the natural language questions associated with the identified one or more entities and the surrounding context to a question and answer service, then receive answers to the natural language questions from the question and answer service. The computer may further determine whether the received answers correctly describe the relation between the identified one or more entities and other entities within the extracted surrounding context.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for identifying information gaps in corpora. A computer receives a document and extracts keywords from the document while filtering trivial keywords. The computer identifies and extracts top keywords detailed by the document using a topic modelling approach before determining whether the extracted top keywords exceed a threshold use frequency. Based on determining that the top keywords exceed a threshold use frequency, determining whether the top keywords have a relation to other entities within the document and, if so, determining whether the top keywords are defined within the document. Based on determining that the top keywords are not defined in the document, adding the top keywords to a list and defining the top keywords.

Abstract: According to an embodiment of the present invention, a system filters a collection of application programming interfaces based on input data representing information of a document to be processed, and generates a pipeline of filtered application programming interfaces. Each filtered application programming interface is sequentially executed within the pipeline. The document may be processed through the pipeline and visualizations based on the processing of the document may be generated, allowing the pipeline to be refined to produce desired output data selected within the visualizations. Embodiments of the present invention further include a method and computer program product for generating a pipeline of filtered application programming interfaces in substantially the same manner described above.