Abstract:
Mechanisms are provided for processing a knowledge canvassing request. The mechanisms receive a request specifying an entity of interest from an originator of the request and analyze the request to extract a feature of the request. The mechanisms determine whether the request is a targeted natural language question to be answered or a knowledge canvassing request, based on the extracted feature. In response to determining that the request is a knowledge canvassing request, the mechanisms process the request by identifying entities represented in a knowledge graph data structure as being related to the entity of interest. The mechanisms output results of the processing of the request to the originator of the request.
Abstract:
An approach is provided in which a knowledge manager identifies a first cohort type and a second cohort type corresponding to an entity included in a question. The knowledge manager determines inferred states to the question by comparing a first set of cohort attributes corresponding to a first cohort type against entity attributes corresponding to the question. In turn, the knowledge manager generates possible answers by comparing the inferred states against a second set of cohort attributes corresponding to a second cohort type.
Abstract:
Mechanisms are provided in a data processing system for utilizing algorithms based on categories in a question answering system. The mechanisms capture a history of performance and correctness metrics for identifying efficiency of respective algorithms for finding answers to questions in respective question categories in a question answering system. The mechanisms determine sets of algorithms to use for respective question categories according to efficiency and correctness analysis. The mechanisms determine a question category of a given input question and execute a set of algorithms corresponding to the question category of the given input question that meet an efficiency threshold to contribute to finding a correct answer for the given input question.
Abstract:
An approach is provided for evaluating subject matter experts (SMEs) in a question and answering (QA) system. In the approach, a number of responses are received at the QA system with each of the responses being a response to a common question and each of the responses being received from a SME. One of the responses is selected with the selected response being from one of the SMEs that is being evaluated. The approach evaluates the selected response by comparing the selected response to the responses received from the other SMEs. Based on the evaluation, the approach updates a SME confidence score that corresponds to the selected SME.
Abstract:
Mechanisms are provided for generating an answer for an input question when the answer is not directly present in a corpus of information. An input question is received from a computing device and analyzed to determine whether the input question is requesting an answer that is calculable. In response to a determination that the input question is requesting an answer that is calculable, one or more constituent data values are retrieved, from a corpus of information, for calculating the requested answer to the input question. A value corresponding to the requested answer is calculated based on the one or more retrieved constituent data values and is then output as the requested answer to the input question.
Abstract:
Mechanisms are provided for generating an answer to an input question. An input question is received and a set of candidate answers is generated along with, for each candidate answer in the set of candidate answers, a corresponding selection of one or more selected evidence portions from a corpus of information providing evidence in support of the candidate answer being a correct answer for the input question. The candidate answers are ranked based on an application of a justifying passage model (JPM) to the selected evidence portions for each of the candidate answers in the set of candidate answers. The JPM identifies whether a candidate answer is justified by a selected evidence passage corresponding to the candidate answer. A candidate answer is output as the correct answer for the input question based on the ranking of the candidate answers.
Abstract:
Mechanisms are provided for generating an answer to an input question. An input question is received and a set of candidate answers is generated along with, for each candidate answer in the set of candidate answers, a corresponding selection of one or more selected evidence portions from a corpus of information providing evidence in support of the candidate answer being a correct answer for the input question. The candidate answers are ranked based on an application of a justifying passage model (JPM) to the selected evidence portions for each of the candidate answers in the set of candidate answers. The JPM identifies whether a candidate answer is justified by a selected evidence passage corresponding to the candidate answer. A candidate answer is output as the correct answer for the input question based on the ranking of the candidate answers.
Abstract:
An approach is provided in which a knowledge manager identifies a first cohort type and a second cohort type corresponding to an entity included in a question. The knowledge manager determines inferred states to the question by comparing a first set of cohort attributes corresponding to a first cohort type against entity attributes corresponding to the question. In turn, the knowledge manager generates possible answers by comparing the inferred states against a second set of cohort attributes corresponding to a second cohort type.
Abstract:
Mechanisms are provided for generating an answer to an input question. An input question is received and a set of candidate answers is generated along with, for each candidate answer in the set of candidate answers, a corresponding selection of one or more selected evidence portions from a corpus of information providing evidence in support of the candidate answer being a correct answer for the input question. The candidate answers are ranked based on an application of a justifying passage model (JPM) to the selected evidence portions for each of the candidate answers in the set of candidate answers. The JPM identifies whether a candidate answer is justified by a selected evidence passage corresponding to the candidate answer. A candidate answer is output as the correct answer for the input question based on the ranking of the candidate answers.
Abstract:
Mechanisms are provided, in association with a question and answer system, for generating answers to an input question. An input question is received and processed to generate at least one query. The at least one query is applied to the corpus to generate a set of candidate answers and corresponding selections of evidence portions of the corpus of information providing evidence in support of the at least one candidate answer being a correct answer for the input question. A graphical user interface (GUI) is output comprising a first GUI sub-section comprising the set of candidate answers, and a second GUI sub-section comprising the evidence portions of the corpus. User input modifying at least one of set of candidate answers or the evidence portions of the corpus of information is received via the GUI and an operation of the data processing system is adjusted based on the user input.