Abstract: A system includes a question processing circuit, an answer processing circuit, a mining circuit, and a question determination circuit. The question processing circuit is configured to receive a first question. The answer processing circuit is configured to generate a first answer set corresponding to the first question. The first answer set corresponds with one or more evidence passages. The mining circuit is configured to mine the evidence passages to identify a geospatial or temporal modifier. The question determination circuit is configured to generate a second question based on the first question and the geospatial or temporal modifier. The answer processing circuit is further configured to generate a second answer set corresponding to the second question and return a question answer set based on the second answer set to a user.

Abstract: A system for question answering (QA) documents data ingestion decides to ingest the documents data through a first plurality of sub-pipelines including a first sub-pipeline having a first set of engines and a second sub-pipeline having a second set of engines being independent from the first set of engines. The system determines a subset of the documents data and decides to ingest the subset through a second plurality of sub-pipelines including a third sub-pipeline having a third set of engines and a fourth sub-pipeline having a fourth set of engines being independent from the third set of engines. A set of engines of the second plurality of sub-pipelines and a set of engines of the first plurality of sub-pipelines are in a common class. The system selects output data from the second plurality of sub-pipelines over corresponding output data from the first plurality of sub-pipelines and generates a knowledge base.

Abstract: A method, system and computer program product are provided for implementing unstructured content utilization from a structured source in a system capable of answering questions. A question is received by the system. The question is provided as a list of tokens T (T1, T2, . . . , Tn). A structured source is received containing records R (R1, R2, . . . , Rk). Headers H (H1, H2, . . . , Hi) are mapped to records. Each record R1, R2, . . . , Rk is searched for any token Ti in the list of tokens T (T1, T2, . . . , Tn) in the question. Responsive to identifying the token Ti in the question in a record Rj, the token Ti is added to a tracking structure. Any header mapped to the record Rj is compared to the list of tokens T (T1, T2, . . . , Tn) in the question. Responsive to identifying a header Hj mapped to the record Rj in the question, the header Hj is added to tracking structure.

Abstract: Current plagiarism checkers can determine if a document has extensively copied from another but these checkers fail when a document is filled with synonyms. The present invention offers a means of detecting plagiarism involving the use of synonyms or heaving paraphrasing. A source passage from a pertinent corpus is modified by generating augmented tokens which include synonyms for the various terms in the passage. Text analysis may be required to confirm the semantic meaning of a term. The modified passage may be a regular expression. The modified passage can then be compared to a suspect passage using a trigram scorer. If possible plagiarism is detected, an alert message is sent to a reviewer with the passage of interest, the source passage, and an identification of the related corpus.

Abstract: An approach is provided that receives words that are input by a user of an application with the words being displayed on a display device. Each of the words are compared to words from a dictionary. Based on the comparisons, words that are not found in the dictionary and only appear a single time are highlighted as being misspelled words. However, words that are not in the dictionary but appear multiple times in the document are highlighted differently to indicate that these words are possible misspelled words with the difference in highlighting allowing the user to easily discern between misspelled and possibly misspelled words.

Abstract: An approach is provided that receives words that are input by a user of an application with the words being displayed on a display device. Each of the words are compared to words from a dictionary. Based on the comparisons, words that are not found in the dictionary and only appear a single time are highlighted as being misspelled words. However, words that are not in the dictionary but appear multiple times in the document are highlighted differently to indicate that these words are possible misspelled words with the difference in highlighting allowing the user to easily discern between misspelled and possibly misspelled words.

Abstract: An approach is provided in which an information handling system identifies candidate answers from a knowledge base that correspond to a question comprising a lexical answer type (LAT). The information handling system determines sub-LATs corresponding to the LAT in a database that are child LATs of the LAT. The information handling system then identifies a set of the candidate answers that correspond to at least one of the sub-LATs and ranks the set of candidate answers based on one or more ranking criterion. In turn, the information handling system provides the ranked set of candidate answers to a user.

Abstract: A system for handling a graphical representation of data associated with a question answering (QA) input document includes a memory having instructions therein and includes at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to derive, at least from a portion of the QA input document, first metadata regarding a context of the graphical representation of data. The at least one processor is also configured to execute the instructions to derive, at least from a portion of the graphical representation of data, tabular data. The at least one processor is also configured to execute the instructions to determine, at least in part by comparing at least a portion of the first metadata to existing table annotations from a QA knowledge base, how to incorporate the tabular data into the QA knowledge base.

Abstract: Adapting a polar question to a form answerable by a non-polar question answering system. Entities are identified in the polar question. A set of non-polar questions are generated by removing an entity and using the remaining entities to form a set of questions with the removed entities as the expected answers. The set of non-polar questions are presented to a non-polar question answering system, and a set of answers are received. The set of answers are scored to determine a polar answer to the polar question.

Abstract: A method trains an artificial intelligence system to respond to a complex query. A query/answer (Q/A) system sends a first query to an information server, where the first query is a query about a first topic with regard to a first entity, and where the information server provides access to unstructured information sources. In response to receiving a negative response to the first query for the first entity, the Q/A system sends variations of the first query and a second query about a second topic to the information server. The Q/A system identifies a pattern in the table of information in order to create the answer to the first query for the first entity. The Q/A system then trains an artificial intelligence system to respond to a complex query about the first entity with information in the table of information.

Abstract: A method trains a neural network to identify an event based on discrepancies in answers to factoid questions at different times. One or more processors identify answers to a series of factoid questions. The processor(s) compare the answers from the series of factoid questions in order to determine discrepancies in the answers at different times, and then train a neural network to identify an event based on the discrepancies in the answers at the different times.

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: 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 method, system and computer program product are provided for implementing misleading title identification. A title and a list of passages are received. The title is supplied to a question answering factoid pipeline as a question. The title is analyzed against the list of passages or content as an answer source material. A respective answer score of all passages is compared with a tunable threshold to identify titles that are misleading or inaccurate based on the content of all passages. A selected action for the identified misleading titles is provided for a user.

Abstract: In response to receiving a second verification record of a second location and a second time at which a user is verified as present at the second location by a second internet of things (IoT) device based on biometric input recognition performed by a second IoT service to the second IoT device, a proximity service maintains the second verification record in a user location database in association with a user identifier for the user only if travel between the second location and a first location previously recorded at a first time prior to the second time is feasible as determined by a mapping service, the second IoT device for performing another service using a biometric input separate from generating and transmitting the verification record based on the biometric input.

Abstract: A method of augmenting an information retrieval method including receiving a query, parsing the query to generate an instance graph, providing a plurality of constraint graphs, organized into at least two ranks, each constraint graph associated with a focus, determining at least one of the constraint graphs matching a structure of the instance graph, and annotating the query with the focus of each matching constraint graph of a highest rank among all matching constraint graphs.

Abstract: Embodiments provide a computer implemented method for ranking supporting passages in a question answering (QA) system. The method includes the following steps: receiving an input question and a plurality of passages, wherein the plurality of passages are extracted from the document corpus by the QA system; identifying a plurality of candidate answer occurrences from the plurality of passages; assigning a plurality of first local features to each candidate answer occurrence; merging the plurality of candidate answer occurrences to generate a group of candidate answers; assigning a plurality of second local features and a plurality of nonlocal features to each candidate answer; ranking the group of candidate answers using a linear answer scoring model; and ranking the plurality of candidate answer occurrences using the linear answer scoring model.

Abstract: Embodiments provide a computer implemented method for identifying and correcting a misspelling in a question answering (QA) system, wherein the QA system is coupled to a document corpus, and the document corpus includes a plurality of documents related to a particular domain. The method includes the following steps: receiving an input question and a plurality of passages, wherein the plurality of passages are extracted from the document corpus by the QA system; providing at least one alternate form for each token extracted from the input question and the plurality of passages; identifying at least one misspelled token; and scoring at least one alternate form of each identified misspelled token.

Abstract: Embodiments for processing questions based on equivalence classes in a cognitive question answering system. A plurality of syntactic representations of a plurality of questions asked of the cognitive question answering system are provided. A plurality of syntactic representations of a plurality of passages ingested by the cognitive question answering system are provided. Question focus to candidate passage pairs are mapped to form an equivalence class mapping, and the equivalence class mapping is used to determine an answer to one of the plurality of questions asked of the cognitive question answering system.

Abstract: An approach is provided in which a knowledge manager identifies training entities in a training question answer pair and identifies multiple database paths a database that link the training entities. The knowledge manager then generates multiple generalized queries based upon the identified multiple database paths and assigns query scores to the multiple generalized queries. 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 custom queries from the generalized queries and queries the database using the custom queries. The knowledge manager, in turn, scores answers generated from the custom queries based upon the custom queries' corresponding query scores.