Details and Options

• In FindTextualAnswer[text,…], text can be a string, a file with plain text, a ContentObject expression or a list of these text objects.
• FindTextualAnswer[text,{"question₁","question₂",…},…] gives answers for each of the question_i.
• The property prop can be one of the following:
• "String"substring corresponding to candidate answer "Probability"
• estimated probability that the answer is correct
"Position"
• start and end positions in text of the answer
"Sentence"sentence containing the candidate answer "Line"line containing the candidate answer "Paragraph"paragraph containing the candidate answer "HighlightedSentence"sentence with candidate answer highlighted "HighlightedLine"line with candidate answer highlighted "HighlightedParagraph"paragraph with candidate answer highlighted {prop₁,prop₂,…}a list of property specifications
• The following option can be given:
• TargetDevice "CPU"target device on which to perform the computation PerformanceGoal Automaticwhich aspects of performance to optimize
• Possible settings for PerformanceGoal include "Speed" and "Quality".
• FindTextualAnswer uses statistical methods to try to find answers. Details of the text and question can affect its performance.
• FindTextualAnswer may download resources that will be stored in your local object store at $LocalBase, and that can be listed using LocalObjects[] and removed using ResourceRemove.

Examples

Basic Examples  (2)

Answer a question from a sentence:

Answer a question from a paragraph:

Scope  (6)

Find multiple possible answers from a text:

Find multiple possible answers along with their probability:

Answer several questions:

Find the sentence containing the answer:

Get the position of the answer in the question:

Answer several questions and display the answers in context:

Look for the answer to a question from a ContentObject expression:

Options  (2)

PerformanceGoal  (1)

Use PerformanceGoal"Quality" to get a more accurate answer:

TargetDevice  (1)

Answer questions using the default system GPU, if available:

The computation is typically faster than with CPU:

If a compatible GPU is not available, a message is issued:

Applications  (1)

Search an Answer to a General Question in Wikipedia  (1)

Display in context the possible answers from a Wikipedia search:

The instances of the same names can be grouped along with their probabilities:

Then the one with the largest total sum of probability is probably the good answer:

Possible Issues  (1)

FindTextualAnswer is able to understand semantic concepts to some extent but is not able to use logic to guess a number: