Abstract: A controller generating a knowledge graph of entries, each entry comprising a separate entity identifier and a separate entity mention identifier within a separate document of a corpus of documents with a located relationship and one or more computed prefix-based geotemporal values determined from geotemporal information associated with the separate entity mention identifier within the separate document. The controller, in response to receiving an input comprising a particular entity and a threshold value, mapping the threshold value to a geospatial hash prefix type and a temporal hash prefix type. The controller applying geospatial hash prefix type and the temporal hash prefix type to the entries in the knowledge graph to determine a response to the input indicating one or more geotemporal proximate entities identified within a degree of geotemporal proximity to the particular entity set by the threshold value.

Abstract: A system, computer program product, and method are provided for use with an intelligent computer platform to identify intent and convert the intent to one or more physical actions. The aspect of converting intent includes receiving content, identifying potential variants, and statistically analyzing the variants with a confidence assessment. The variants are sorted based on a protocol associated with the confidence assessment. A variant from the sort is selected and applied to a physical device, which performs a physical action and an associated hardware transformation based on the variant.

Abstract: A method learns approximate translations of unfamiliar measurement units during deep question answering (DeepQA) system training and usage. The DeepQA system receives a training set containing Question-Answer (QA) pairs having known unit-of-measurement terms, where each QA pair contains an answer having a known numeric value for a corresponding question from the QA pair. The DeepQA system receives a question from each QA pair from the training set to the DeepQA system in order to find answers and passage phrases to the question from each QA pair, and then identifies all found answers and passage phrases having values that are within a predetermined range of answer values of the training set, where one or more of the identified all found answers and passage phrases contain unfamiliar unit-of-measurement terms, in order to learn approximate translations of the unfamiliar unit-of-measurement terms.

Abstract: A controller, responsive to detecting geospatial and temporal information associated with a mention of an entity in a document, for converting the geospatial information into a specified geospatial format and the temporal information into a specified temporal format. The controller for computing prefix-based geospatial values for the converted geospatial information and prefix-based temporal values for the converted temporal information. The controller for encoding an entry in a knowledge graph for the mention of the entity from the document with the prefix-based geospatial values and the prefix-based temporal values, wherein each digit of the prefix-based geospatial values and the prefix-based temporal values in the knowledge graph that matches another one or more prefix-based geospatial values and another one or more prefix-based temporal values in another entry for another entity mention in the knowledge graph reflects a degree of granularity of geotemporal proximity of the entity and the another entity.

Abstract: A controller accesses an initial taxonomy for a domain comprising one or more existing terms for the domain identified in a hierarchical structure. The controller analyzes a corpus documents for a domain to identify a selection of one or more documents with glossaries. The controller extracts, from the glossaries, one or more pairs each comprising a term and a definition. The controller attempts to map a respective term of each of the one or more pairs into the initial taxonomy for the domain based on text of a respective definition of each of the one or more pairs to generate an updated taxonomy for the domain.

Abstract: A method utilizes a deep question answering (QA) system to provide an answer, to a certain type of question, that includes an unfamiliar measurement unit. An answer key is utilized to train a DeepQA system to search for passages that answer a certain type of question, where the DeepQA system outputs an answer key value and an answer key measurement unit that is associated with the answer key value. The method identifies a candidate answer that includes a candidate passage containing the answer key value but not the answer key measurement unit, where a candidate passage measurement unit in the candidate passage is associated with the answer key value. The method then matches the answer key measurement unit to the candidate passage measurement unit based on the answer key measurement unit and the candidate passage measurement unit both being associated with the answer key value.

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: A method, computer system, and a computer program product for converting a plurality of factoid answers into a plurality of structured relations for storage in a structured knowledge base is provided. The present invention may include receiving a query from a user. The present invention may also include generating a plurality of possible factoid answers. The present invention may then include determining a plurality of confidence scores for the plurality of possible factoid answers. The present invention may then include generating a plurality of certain factoid answers from the plurality of possible factoid answers. The present invention may then include identifying a plurality of special target items. The present invention may further include generating a plurality of structured relations for each certain factoid answer and the identified plurality of special target items. The present include may also include storing the generated plurality of structured relations into the structured knowledge base.

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 service, in response to receiving a question in a natural language format, identifies one or more selected passages from a corpus that are relevant to a focus of the question from among multiple passages in the corpus. The service aligns one or more answer grammatical properties of one or more answers, selected from the one or more selected passages, to one or more question grammatical properties of the focus of the question. The service returns the one or more answers in response to the question.

Abstract: Method and apparatus improves the quality of responses from an automatic dialogue system by dynamically adjusting response thresholds. More particularly, the automatic dialogue system may dynamically determine response threshold values in response to user feedback. The response threshold values may be used to evaluate a confidence value. The confidence value may be assigned to or otherwise associated with an input class, or user intent. The system may automatically adjust the response threshold values to provide a better user experience as the amount of user-interaction with the system increases.

Abstract: A system and a computer program product are provided for evaluating question-answer pairs in an answer key by generating a predicted answer to a test question based on the answer key modification history for comparison matching against a generated answer that is generated in response to the test question, and then comparing the predicted answer and generated answer to determine an accuracy score match indication therebetween so as to present an indication that the answer key may have a problem if there is a match between the predicted answer and generated answer.

Abstract: A system and a computer program product are provided for evaluating question-answer pairs in an answer key by generating a predicted answer to a test question based on the answer key modification history for comparison matching against a generated answer that is generated in response to the test question, and then comparing the predicted answer and generated answer to determine an accuracy score match indication therebetween so as to present an indication that the answer key may have a problem if there is a match between the predicted answer and generated answer.

Abstract: A controller accesses an initial taxonomy for a domain comprising one or more existing terms for the domain identified in a hierarchical structure. The controller analyzes a corpus documents for a domain to identify a selection of one or more documents with glossaries. The controller extracts, from the glossaries, one or more pairs each comprising a term and a definition. The controller attempts to map a respective term of each of the one or more pairs into the initial taxonomy for the domain based on text of a respective definition of each of the one or more pairs to generate an updated taxonomy for the domain.

Abstract: An approach is provided in which an information handling system analyzes a message tone vector corresponding to a message against a target tone vector corresponding to a recipient of the message. The message tone vector includes a set of message tone attributes and the target tone vector includes a set of target tone thresholds. The information handling system, in response to determining a difference between the message tone vector and the target tone vector, creates a variant message by substituting words in the message with one or more similar words based on the target tone vector. In turn, the information handling system sends the variant message to the recipient.

Abstract: A device includes a processor configured to, in response to determining that an input phrase includes a first term that is included in a term hierarchy, generate a second phrase by replacing the first term in the input phrase with a second term included in the term hierarchy. The processor is configured to determine that interactive response (IR) training data indicates that the input phrase is associated with a user intent indicator. The processor is configured to determine that user interaction data indicates that a first proportion of user phrases received by an IR system correspond to the user intent indicator. The processor is configured to update speech-to-text training data based on the input phrase and the second phrase so that a second proportion of training phrases of the speech-to-text training data correspond to the user intent indicator. The second proportion is based on the first proportion. A speech-to-text model is trained based on the speech-to-text training data.

Abstract: A service receives, from a query entity store, a query store result in response to an initial query referencing at least one of a name element and a first identifier component related to an entity, the query store result comprising a query store record comprising information related to the entity. The service receives, from a target entity store, a target store result to a target store query referencing the query store record, the target store result comprising one or more target store records related to the information found in the query store record. The service compares the one or more target store records to the information in the query store record. The service, responsive to determining a relevancy assessment indicates a match between the information in the query store record and two or more particular target store records from among the one or more target store records, triggers the target entity store to merge the two or more particular target store records.

Abstract: A service, in response to receiving a question in a natural language format, identifies one or more selected passages from a corpus that are relevant to a focus of the question from among multiple passages in the corpus. The service aligns one or more answer grammatical properties of one or more answers, selected from the one or more selected passages, to one or more question grammatical properties of the focus of the question. The service returns the one or more answers in response to the question.

Abstract: A method learns approximate translations of unfamiliar measurement units during deep question answering (DeepQA) system training and usage. The DeepQA system receives a training set containing Question-Answer (QA) pairs having known unit-of-measurement terms, where each QA pair contains an answer having a known numeric value for a corresponding question from the QA pair. The DeepQA system receives a question from each QA pair from the training set to the DeepQA system in order to find answers and passage phrases to the question from each QA pair, and then identifies all found answers and passage phrases having values that are within a predetermined range of answer values of the training set, where one or more of the identified all found answers and passage phrases contain unfamiliar unit-of-measurement terms, in order to learn approximate translations of the unfamiliar unit-of-measurement terms.

Abstract: A method utilizes a deep question answering (QA) system to provide an answer, to a certain type of question, that includes an unfamiliar measurement unit. An answer key is utilized to train a DeepQA system to search for passages that answer a certain type of question, where the DeepQA system outputs an answer key value and an answer key measurement unit that is associated with the answer key value. The method identifies a candidate answer that includes a candidate passage containing the answer key value but not the answer key measurement unit, where a candidate passage measurement unit in the candidate passage is associated with the answer key value. The method then matches the answer key measurement unit to the candidate passage measurement unit based on the answer key measurement unit and the candidate passage measurement unit both being associated with the answer key value.