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Question-answer system QA-system Start

Lecture



QA-system Start.

l http://start.csail.mit.edu

l Created at MIT Artificial Intelligence Laboratory in

1993 under the leadership of Boris Katz

l Universal

l Uses English l Knowledge Sources:

l local storage (Knowledge Base)

l internet network

l Start System Foundations: l Use specific NLP methods developed specifically for the Start system.

l The idea of ​​creating annotations in natural languages ​​to blocks of information

Start. Types of questions

l Definition Questions:

l What is a fractal?

l Questions about the facts:

l Who invented the telegraph?

l Relationship Issues:

l What country is bigger, Russia or USA?

l List requests:

l Show me some poems by Alexander Pushkin

l ...

Start. Sample Questions

1. Geography

• Give me the state of Colorado.

• What's the largest city in Florida?

• Show me a map of Denmark

• List some large cities in Argentina

• Which is the Baltic Sea or the North Sea?

• Show the capital of the 2nd largest country in Asia

2. Art

• When was Beethoven born?

• Who composed the opera Semiramide?

• What movies has Dustin Hoffman been in?

Start. Sample Questions

3. Science and background information

• What is Jupiter's atmosphere made of?

• Why is the sky blue?

• Convert 100 dollars into Euros • How is the weather in Boston today?

• How far is Neptune from the sun?

• Show me a metro map of Moscow.

4. History and culture

• What countries speak Spanish?

• Who was the fifth president of the United States?

• What languages ​​are spoken in the most populous country in Africa?

• How many people live on Earth?

Start. Knowledge base

  Question-answer system QA-system Start

Start. Knowledge base

l Consists of 3 parts:

l Ternary expressions (T-expressions)

l Syntax / semantic inference rules (S-rules)

l Catalog of words (Lexicon)

Start. Ternary expressions

l T-expressions are expressions of the form.

<subject relationship object>

l Other T-expressions can act as an object / subject of a single T-expression.

l Adjectives, possessive pronouns, prepositions and other parts of the sentence are used to create additional T-expressions.

l The remaining attributes of the sentence (articles, tenses of verbs, adverbs, auxiliary verbs, punctuation marks, etc.) are stored in a special History structure associated with a T-expression.

Start. T-expression example

“Bill surprised Hillary with his answer”

   Question-answer system QA-system Start

<< Bill surprise Hillary> with answer> <answer related-to Bill>

Start. Request Processing with T-Expressions

“Whom did Bill surprise with his answer?”

Question Analyzer

“Bill surprised whom with his answer?”

Parser

<< Bill surprise whom> with answer>

<answer related-to Bill>

Knowledge base

Whom = hillary

<< Bill surprise Hillary > with answer>

<answer related-to Bill>

Generator

“Bill surprised Hillary with his answer”

Start. Request Processing with T-Expressions

“Did Bill surprise with his answer?”

Question Analyzer

“Bill surprised Hillary with his answer?”

Parser

<< Bill surprise Hillary> with answer>

<answer related-to Bill>

Knowledge base

Yes!

Generator

“Yes, Bill Surprised Hillary with his answer”

T-expressions vs. keywords

l The bird ate the young snake

The snake ate the young bird

l The meaning of life

A meaningful life

l The bank of the river

The bank near the river

T-expressions vs. keywords

l Keywords:

l Loss of information about semantic connections between words.

l Texts are not compared with semantic features, but according to the statistical characteristics of keywords

l T-expressions:

l Reflect the word order in the sentence and the semantic connections between them.

l The expressive power of T-expressions is enough to write annotations in natural languages.

l Effective when indexing

What do frogs eat?

l Search based on T-expressions gave 6 answers, of which 3 are correct:

l Adult frogs eat mainly animals, including earthworms, minnows, and spiders

l One group of South American frogs feeds mainly on other frogs

l Frogs eat many other animals, including spiders, flies, and worms

l ...

What do frogs eat?

l Search based on keywords yielded 33 results, which also met the answers to the question “What eats frog?” and just the matches of the words “eat” and

“Frog”:

l Bowfins eat mainly other fish, frogs, and crayfish

l Cranes eat a variety of foods, including frogs, fishes, birds, and various small mammals.

l ...

Start. S-rules

Problem:

“Bill's answer surprised Hillary” = “Bill's surprised Hillary with his answer”

<answer surprise Hillary> << Bill surprise Hillary> with answer>

<answer related-to Bill> = <answer related-to Bill>

  Question-answer system QA-system Start

Start. S-rules

l S-rules describe linguistic variations:

l Lexical

l Synonyms

l Morphological

l Words with the same root

l syntactic

l Inversions

l Active / passive voice

l Possessive adjectives

l Also used to describe logical implications.

  Question-answer system QA-system Start

m   Question-answer system QA-system Start

Start. S-rules

l Some S-rules can be used in 2 directions:

l live

l when updating the knowledge base with new expressions

l in reverse

l when processing a user request

Start. Lexicon

l Some S-rules apply to groups of words.

l In Lexicon contains a list of words of the language, and for each word is a list of groups to which it belongs

  Question-answer system QA-system Start


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Creating question and answer systems

Terms: Creating question and answer systems