Abstract: Embodiments are directed to an entity extraction and filtering system that enables a close search of documents to build filters necessary for near real-time monitoring of streaming sources of information. According to an embodiment, the entity extraction and filtering system operates based on the following parameters. First, a detection of an entity of interest warrants flagging an arriving article for analyst attention. Nothing more than a match may be required. The list of entities may be derived by an entity extractor from a corpus of data. Secondly, automatic updates may be utilized, so that exports are automatically updated to the filters. Thirdly, information flowing past the filters may update a static corpus whether or not they are flagged for an analyst or user. This allows for new relationships to be detected and extracted, and the filters subsequently updated.

Abstract: A mechanism is provided in a data processing system for identifying nonsense passages. An annotator in a natural language processing pipeline configured to execute in the data processing system annotates an input passage in a corpus with linguistic features to form an annotated passage. A domain-specific policy is associated with a domain of the corpus. A metric counters component in the natural language processing pipeline counts a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts. The metric counters component of the natural language processing pipeline determines a value for a metric based on the set of feature counts. The metric is specified in the domain-specific policy. A comparator component of the natural language processing pipeline compares the value for the metric to a predetermined model threshold. The threshold is specified in the domain-specific policy.

Abstract: According to one embodiment, a method, computer system, and computer program product for acronym resolution is provided. The present invention may include receiving documents; identifying explicit expansions within the documents; receiving an input from a user; retrieving passages relevant to the received input from the documents; for each acronym within the one or more relevant passages, determining whether the acronym corresponds with explicit expansions within the relevant passages; for each of the acronyms that do not correspond with explicit expansions, determining whether the acronym corresponds with implicit expansions within the relevant passages; and for each of the acronyms that do not correspond with implicit expansions, determining whether the acronym corresponds with acronyms within a universal acronym list, and transmitting the one or more resolved acronyms to a question answering system.

Abstract: A method, system and a computer program product are provided for scoring candidate answers for geographic relevance by identifying document location information that is associated with a document, associating each token in the document with the document location information, and then comparing geographic foci identified for a candidate answer from the tokens with geographic foci identified for an input question to generate a geographic relevance score for the candidate answer to the input question.

Abstract: Dynamic semantic processing of text in a word processing application with engagement of question-answering system. A user provides a text stream to a computer system via an input source. The input text stream includes a first natural language statement. The system determines that the first natural language statement includes a fact-based component expressed in natural language form. The system identifies an initial span and an alternative span of the first natural language component, based on the determining. The system engages a question-answering (QA) system by providing the initial span and the alternative span of the first natural language component to the QA system, and by receiving, in response to the providing, a set of natural language results from the QA system. The system evaluates the initial span and the alternative span of the first natural language component based on the received natural language results.

Abstract: Embodiments are directed to interaction with an open-domain question and answer system to seek answers to broad and general questions by providing templates and words or phrases to fill slots in the templates that specify alternative specific questions, the answer to any of which may serve the broader purpose. Responses to all of the questions in a batch are considered as candidates, with the strongest general answers being returned. The approach, according to embodiments herein, addresses the need for responses to broad questions in which the user is seeking any response to a known pattern. The user is able to articulate the question as a template that can be instantiated in many forms, and the user may specify how strongly the concrete answers indicate an answer to the underlying general question.

Abstract: Embodiments are directed to interaction with an open-domain question and answer system by recognizing questions that are highly broad or abstract, and generating and processing a batch of questions expressing alternate, concrete instances of the more general, abstract question. Responses to all of the questions in the batch are considered as candidates, and the strongest general answers are returned. A weighted, ranked answer set, based on weighting individual concrete questions and scaling the answers proportional to the weight of the questions, is provided to the user. The approach, according to embodiments herein, addresses the need for responses to broad questions in which a response to any of a set of more concrete question instances may serve to answer the question.

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 an enhanced corpus management system, the method comprising: identifying one or more functional domain categories; ingesting one or more incoming documents to form an open-domain corpus; for each functional domain category, identifying one or more representative documents to establish a seed sub-corpus; calculating a degree of fit score between each of the one or more incoming documents and the one or more established functional domain category seed sub-corpora; and assigning one or more of the incoming documents to one or more of the functional domain categories based upon the degree of fit score to create an enhanced corpus.

Abstract: Dynamic semantic processing of text in a word processing application with engagement of question-answering system. A user provides a text stream to a computer system via an input source. The input text stream includes a first natural language statement. The system determines that the first natural language statement includes a fact-based component expressed in natural language form. The system identifies an initial span and an alternative span of the first natural language component, based on the determining. The system engages a question-answering (QA) system by providing the initial span and the alternative span of the first natural language component to the QA system, and by receiving, in response to the providing, a set of natural language results from the QA system. The system evaluates the initial span and the alternative span of the first natural language component based on the received natural language results.

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 an enhanced corpus management system, the method comprising: identifying one or more functional domain categories; ingesting one or more incoming documents to form an open-domain corpus; for each functional domain category, identifying one or more representative documents to establish a seed sub-corpus; calculating a degree of fit score between each of the one or more incoming documents and the one or more established functional domain category seed sub-corpora; and assigning one or more of the incoming documents to one or more of the functional domain categories based upon the degree of fit score to create an enhanced corpus.

Abstract: An embodiment of the invention may include a method, computer program product and system for generating follow-up questions based on machine learning utilizing a computing device. The embodiment may include receiving an input question from a user. The embodiment may include parsing the received input question to extract input question components. Parsing utilizes natural language processing techniques. The embodiment may include executing trained question component models to predict follow-up question components. The extracted input question components are utilized as inputs to the trained question component models. The embodiment may include combining the predicted follow-up question components to generate one or more follow-up questions. The embodiment may include returning the one or more follow-up questions to the user.

Abstract: Dynamic semantic processing of text in a word processing application with engagement of question-answering system. A user provides a text stream to a computer system via an input source. The input text stream includes a first natural language statement. The system determines that the first natural language statement includes a fact-based component expressed in natural language form. The system identifies an initial span and an alternative span of the first natural language component, based on the determining. The system engages a question-answering (QA) system by providing the initial span and the alternative span of the first natural language component to the QA system, and by receiving, in response to the providing, a set of natural language results from the QA system. The system evaluates the initial span and the alternative span of the first natural language component based on the received natural language results.

Abstract: The present invention may receive the question, a plurality of the candidate answers, and a plurality of documents associated with the plurality of candidate answers in the natural language. Then the present invention may tokenize the question, the plurality of the candidate answers, and the plurality of the documents into a corresponding n-gram sequence. The present invention may map n-gram elements from the tokenized question to the n-gram elements of the plurality of the tokenized candidate answers and the plurality of the tokenized documents using the latent token representation technique. The present invention may score the plurality of tokenized candidate answers based on the latent token representation technique. Then, the present invention may determine the precise answer based on the plurality of scored candidate answers.

Abstract: A system and a method for determining user synonyms in a query processing system is disclosed. A first query is received from a user of the query processing system. The query is processed through the query processing system to generate results for the first query. The user then provides a second query. The system determines a contextual similarity between the first query and the second query. When the first query and the second query are determined to be contextually similar, a first term is identified in the first query that is different from a second term in the second query. Once identified, the system determines if the first term and the second term are not listed as synonyms in the thesaurus. If they are not listed as synonyms they can be added as synonyms to the thesaurus.

Abstract: According to one embodiment, a method, computer system, and computer program product for acronym resolution is provided. The present invention may include receiving documents; identifying explicit expansions within the documents; receiving an input from a user; retrieving passages relevant to the received input from the documents; for each acronym within the one or more relevant passages, determining whether the acronym corresponds with explicit expansions within the relevant passages; for each of the acronyms that do not correspond with explicit expansions, determining whether the acronym corresponds with implicit expansions within the relevant passages; and for each of the acronyms that do not correspond with implicit expansions, determining whether the acronym corresponds with acronyms within a universal acronym list, and transmitting the one or more resolved acronyms to a question answering system.

Abstract: In an approach to watching hypotheses in a deep question answering system, one or more processors receive a question from a user and generate a first result set based on the question. One or more processors receive a request from the user to watch one or more hypothesis answers in the first result set. One or more processors generate a second result set based on the question, where the second result set is generated at a later time than the first result set. One or more processors further determine a similarity score between a hypothesis answer in the second set of one or more hypothesis answers and the watched one or more hypothesis answers and, responsive to determining that the similarity score is below a predetermined threshold, one or more processors send a contradiction alert to the user indicating a potential alternative hypothesis.

Abstract: Embodiments can provide a computer implemented method for harvesting training data for a training set for use by a system capable of answering questions, the system comprising a processor and a memory comprising instructions executed by the processor, the method comprising receiving, from a user, an input question; processing the input question and returning, to the user, a result set comprising one or more ranked hypotheses and one or more ranked evidence passages corresponding to the one or more ranked hypotheses; receiving, from the user, an indication that one of the one or more ranked hypotheses is to be designated a watched hypothesis; adding the input question and the watched hypothesis to a to-be-vetted question/answer (QA) pair set comprising one or more to-be-vetted QA pairs; vetting each of the one or more to-be-vetted QA pairs in the to-be-vetted QA pair set through a first-pass automatic vetting procedure; if a vetted QA pair passes the first-pass automatic vetting procedure, adding the vetted QA

Abstract: A mechanism is provided in a data processing system for identifying nonsense passages. The mechanism annotates an input passage with linguistic features to form an annotated passage. The mechanism counts a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts. The mechanism determines a value for a metric based on the set of feature counts and compares the value for the metric to a predetermined model threshold. The mechanism identifies whether the input passage is a nonsense passage based on a result of the comparison.

Abstract: Embodiments are directed to an entity extraction and filtering method that enables a close search of documents to build filters necessary for near real-time monitoring of streaming sources of information. According to an embodiment, the entity extraction and filtering method operates based on the following parameters. First, a detection of an entity of interest warrants flagging an arriving article for analyst attention. Nothing more than a match may be required. The list of entities may be derived by an entity extractor from a corpus of data. Secondly, automatic updates may be utilized, so that exports are automatically updated to the filters. Thirdly, information flowing past the filters may update a static corpus whether or not they are flagged for an analyst or user. This allows for new relationships to be detected and extracted, and the filters subsequently updated.

Abstract: Embodiments are directed to an entity extraction and filtering system that enables a close search of documents to build filters necessary for near real-time monitoring of streaming sources of information. According to an embodiment, the entity extraction and filtering system operates based on the following parameters. First, a detection of an entity of interest warrants flagging an arriving article for analyst attention. Nothing more than a match may be required. The list of entities may be derived by an entity extractor from a corpus of data. Secondly, automatic updates may be utilized, so that exports are automatically updated to the filters. Thirdly, information flowing past the filters may update a static corpus whether or not they are flagged for an analyst or user. This allows for new relationships to be detected and extracted, and the filters subsequently updated.