Abstract: An approach is provided in which a knowledge manager identifies training entities in a training question answer pair and identifies database paths a database that link the training entities. The knowledge manager then generates a generalized query based upon the identified database paths. In addition, the knowledge manager generates a generalized syntactic pattern based upon syntactic relationships between the training entities in the training question answer pair. When the knowledge manager receives a question and matches the syntactic pattern of the received question to the generalized syntactic pattern, the knowledge manager generates a custom query from the generalized query and queries the database using the custom query.

Abstract: An approach is provided in which an information handling system converts a first set of text to synthesized speech using a text-to-speech converter. The information handling system then converts the synthesized speech to a second set of text using a speech-to-text converter. In response to converting the synthesized speech to the second set of text, the information handling system analyzes the second set of text against a filtering criterion and prevents usage of the synthesized speech based on the analysis.

Abstract: A question answering (QA) system comprising memory for storing instructions, and a processor configured to execute the instructions to ingest source documents that include structured data and unstructured data to create a knowledge base, wherein the unstructured data includes table data; create table annotations to represent the table data; store the ingested structured data, unstructured data, and the table annotations in the knowledge base; and determine answers to questions using the knowledge base.

Abstract: Mechanisms are provided for implementing a proximity based candidate answer pre-processor engine that outputs a sub-set of candidate answers to a question and answer (QA) system. The mechanisms receive a lexical answer type (LAT) and an entity specified in an input natural language question as well as an ontology data structure representing a corpus of natural language content. The mechanisms identify a set of candidate answers having associated nodes in the ontology data structure that are within a predetermined proximity of a node corresponding to the entity, and a sub-set of candidate answers in the set of candidate answers having an entity type corresponding to the LAT. The mechanisms output, to the QA system, the sub-set of candidate answers as candidate answers to the input natural language question for evaluation and selection of a final answer to the input natural language question.

Abstract: A computer-implemented method includes receiving an input query including a comparative question referencing a plurality of entities. The comparative question includes a comparative term regarding a metric associated with the plurality of entities. The computer-implemented method includes generating a plurality of polar questions. Each of the plurality of polar questions seeks a polar answer to a comparison, along the metric and according to the comparative term, between a target entity of the plurality of entities and at least one second entity of the plurality of entities. The computer-implemented method includes determining confidence scores for the plurality of polar questions. The computer-implemented method includes identifying a particular polar question of the plurality of polar questions based on the confidence scores. The computer-implemented method includes outputting a response to the input query that identifies the target entity of the particular polar question as an answer to the input query.

Abstract: A computer-implemented method includes dividing a textual representation of a media content into a plurality of portions separated at temporal boundaries of the media content and performing an analysis of each portion of the plurality of portions of the textual representation of the media content to determine a characteristic associated with each respective portion of the textual representation of the media content, generating a multi-dimensional model assigning each determined characteristic to each associated respective portion of the plurality of portions of the textual representation of the media content, the multi-dimensional model identifying each determined characteristic and the temporal boundaries to enable control of an environmental control device to modify an environment proximate to a user based on the multi-dimensional model, and transmitting the multi-dimensional model to a user equipment configured to control the environmental control device to modify the environment proximate to the user base

Abstract: A cognitive system improves the accuracy of a natural language statement by analyzing relationships between entities in a knowledge graph for the statement. A natural language processing engine extracts entities and relationships in the statement, and a yes/no pipeline gauges the accuracy of the statement. If a statement is deemed inaccurate, the knowledge graph is used to identify a predominant relationship between certain entities, and a candidate phrase representing the predominant relationship is generated and presented to the user as a suggested replacement for a target phrase in the statement representing the relationship. The yes/no pipeline computes an accuracy score for the statement, and the statement is deemed inaccurate when the score is below a programmable threshold. The assertiveness of the system can be tuned by requiring the accuracy score of a proposed modified statement to be greater than the score of the original statement plus some tuning factor.

Abstract: A cognitive assistant system, computer program product, and computer-implemented method configured to improve the accuracy of a statement. In one example, the system receives from a user an original statement that includes statement entities and generates an original confidence estimate (CE) for a correctness of the original statement. The system generates a replacement statement by selecting a suspect statement entity, selecting a replacement entity for the suspect statement entity, and replacing the suspect statement entity with the replacement entity in the original statement. The system generates a replacement CE for a correctness of the replacement statement. If the replacement CE exceeds the original CE by a tuning factor, the system sends the replacement statement to the user. If not, the system repeats generating the replacement statement and generating the replacement CE.

Abstract: A method of augmenting a knowledge graph includes obtaining the knowledge graph, which includes entities and relationships between the entities defining respective edges, clustering the entities into knowledge domains using semantic distances determined between the entities and a threshold on the semantic distances, identifying strengths of the relationships between adjacent entities in the knowledge graph, creating knowledge chains from node pairs in the knowledge graph, including generating a minimum spanning tree using the strengths of the relationships, pruning edges from the knowledge chain using a threshold on weights corresponding to the edges, defining a first knowledge index for each of the knowledge chains, defining a second knowledge index for each of the knowledge domains, and defining a third knowledge index for the knowledge graph as a harmonic mean of a sum of the first knowledge indexes and a sum of the second knowledge indexes.

Abstract: A method includes: receiving a question including multiple foci; determining one or more passages (OMPs) that include one or more sets of candidate answers (OMSCAs) to the question; determining matchings between words in the question and words in the OMPs; determining skipngrams of the question (“first skipngrams”); determining one or more sets of skipngrams of the OMPs (“second skipngrams”); determining one or more matching numbers (OMMNs) for the second skipngrams by determining, for each set of the second skipngrams and using the matchings, a number of the first skipngrams that match skipngrams of the set of skipngrams; determining a feature input to a machine learning model (MLM) using the OMMNs; determining one or more answers (OMAs) to the question by determining, by the MLM, whether the OMSCAs are correct answers to the question based at least in part on the feature input; and sending the OMAs to a user device.

Abstract: A video conferencing system includes a processing device and a memory device and is configured to manage a video conference to manage a video conference feed to a plurality of participant devices. The system includes an interface control module that receives a plurality of video feeds and audio feeds associated with participants to the video conference, and generates a video conference feed including a video conference interface for being displayed to the plurality of participants. The system also includes a context analysis module that analyzes the audio feeds to identify contextual information associated with the conversation. The system further includes a participant modeling module that calculates a topic relevance score for each of the plurality of participants based on the contextual information. During a video conference, the interface control module emphasizes a video feed of a participant associated with a topic relevance score greater than a threshold.

Abstract: A method for merging incoming alerts for accessibility is described. A first input alert and a second input alert intended for presentation by a screen reader are received. If the first input alert and the second input alert have arrived with a specified time interval, the first input alert and the second input alert are combined into an output alert. The output alert is sent to a screen reader for presentation.

Abstract: A computer-implemented method includes receiving a query referencing entities, and determining non-polar questions (NPQs) for the query. Each of the NPQs omits a respective target entity (TE) of the entities. The method includes determining, for each of the NPQs, whether the NPQ is a non-matching NPQ by determining whether a top ranked answer for the NPQ matches the TE of the NPQ. The method includes proceeding to determine an updated input statement (UIS) for a non-matching NPQ by replacing the TE of the non-matching NPQs with the top ranked answer for the non-matching NPQ, determine an updated NPQ for the UIS, and determine whether the top ranked answer for the updated NPQ matches the TE of the updated NPQ, in an iterative or recursive manner. The method includes outputting a UIS as a substitute statement for the query.

Abstract: A method for providing unsupervised entity resolution to a natural language processing system includes receiving a named entity for training from the natural language processing system, searching a corpus for a first undisambiguated named entity corresponding to the named entity, identifying a plurality of disambiguated named entities corresponding to the first undisambiguated named entity, identifying a plurality of aliases for each of the disambiguated named entities, training a classifier for the each of the disambiguated named entities utilizing the aliases identified for respective ones of the disambiguated named entities using the corpus, and resolving the named entity using the classifier, wherein resolving the named entity comprises selecting one of the disambiguated named entities from among the disambiguated named entities and returning, automatically, the selected disambiguated named entity to the natural language processing system.

Abstract: A question and answer (QA) system, computer program product, and computer-implemented method configured to determine an answer to a question that includes a measurement value. In one example, the QA system receives a question and analyzes the question to identify a measurement value specified in the question. The QA system determines relevant passages to the question. The QA system assigns a measurement value confidence score to a relevant passage based on a comparison of the measurement value specified in the question and a second measurement value specified in the relevant passage. The QA system determines an order of the relevant passages using the measurement value confidence score of each of the relevant passages. The QA system determines an answer to the question based on the order of the relevant passages.

Abstract: An apparatus and a computer program product for merging incoming alerts for accessibility are described. Two input alerts intended for presentation by a screen reader are received. If the two input alerts have arrived with a specified time interval, the two input alerts are combined into an output alert. The output alert is sent to a screen reader for presentation.

Abstract: A method for merging incoming alerts for accessibility is described. Two input alerts intended for presentation by a screen reader are received. If the two input alerts have arrived with a specified time interval, the two input alerts are combined into an output alert. The output alert is sent to a screen reader for presentation.

Abstract: A method includes receiving, by a computer system configured to generate search result, a query, identifying a plurality of entities in the query, determining, using a knowledge graph, a measure of a relationship between the entities in the query, identifying a replacement entity for a first entity of the entities in the query, wherein the replacement entity is determined to improve the measure of the relationship between the entities when the first entity is replaced by the replacement entity, and generating a search result using the query modified by the replacement entity, which replaces the first entity in the query.

Abstract: A method for merging incoming alerts for accessibility is described. A first input alert and a second input alert intended for presentation by a screen reader are received. If the first input alert and the second input alert have arrived with a specified time interval, the first input alert and the second input alert are combined into an output alert. The output alert is sent to a screen reader for presentation.

Abstract: Embodiments can provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a mixed-language question answering supplement system, the method comprising receiving a question in a target language; applying natural language processing to parse the question into at least one focus; for each focus, determining if one or more target language verbs share direct syntactic dependency with the focus; for each of the one or more verbs sharing direct syntactic dependency, determining if one or more target language entities share direct syntactic dependency with the verb; determining one or more Abstract Universal Verbal Types associated with each verb; for each of the one or more Abstract Universal Verbal Types, determining whether a dependency between a source language entity and a source language verb is of the same type as the dependency between the target language verb and the ta