Contextual question answering using human chat logs

A system for answering a natural language question, the system comprising:

• a memory having instructions therein;
• and
• at least one processor in communication with the memory, wherein the at least one processor is configured to execute the instructions to:
• receive the natural language question;
• determine, using a support vector machine, a set of most relevant chat session logs to the natural language question from a chat log comprising a plurality of chat session logs;
• concatenate question and answer pairs in each of the set of most relevant chat session logs into a respective plurality of conceptual pseudo-documents;
• determine, using the one or more machine reading comprehension (MRC) models, a probability for a start word and an end word for each of a plurality of non-overlapping text spans comprising one or more of the concatenated question and answer pairs for each of the respective plurality of conceptual pseudo-documents;
• determine a respective plurality of non-overlapping text spans most relevant to the natural language question within each of a respective plurality of conceptual pseudo-documents;
• determine, using the one or more MRC models, a most relevant non-overlapping text span to the natural language question from the plurality of non-overlapping text spans of the respective plurality of conceptual pseudo-documents;
• extract a most relevant question-answer pair to the natural language question from the most relevant pseudo-document based upon the determined probability;
• and
• convey the most relevant question-answer pair to a user device, wherein each one of the conceptual pseudo-documents corresponds to a respective one of the most relevant chat session logs in the set of most relevant chat session logs.

A computer program product for answering a natural language question, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by at least one processor of a system to cause the system to:

• receive the natural language question;
• determine, using a support vector machine, a set of most relevant chat session logs to the natural language question from a chat log comprising a plurality of chat session logs;
• concatenate question and answer pairs in each of the set of most relevant chat session logs into a respective plurality of conceptual pseudo-documents;
• determine, using the one or more machine reading comprehension (MRC) models, a probability for a start word and an end word for each of a plurality of non-overlapping text spans comprising one or more of the concatenated question and answer pairs for each of the respective plurality of conceptual pseudo-documents;
• determine a respective plurality of non-overlapping text spans most relevant to the natural language question within each of a respective plurality of conceptual pseudo-documents;
• determine, using the one or more MRC models, a most relevant non-overlapping text span to the natural language question from the plurality of non-overlapping text spans of the respective plurality of conceptual pseudo-documents;
• extract a most relevant question-answer pair to the natural language question from the most relevant pseudo-document based upon the determined probability;
• and
• convey the most relevant question-answer pair to a user device, wherein each one of the conceptual pseudo-documents corresponds to a respective one of the most relevant chat session logs in the set of most relevant chat session logs.