Natural Language Query Interface

Mostafa Karkache & Bryce Wenninger

Outline Natural Language Query Interface Introduction

What is Natural Language Query Interface? Why do we need this type interface?

Problems implementing this interface. Ambiguity i.e. Semantics Size of the language Syntax And Grammars Anaphora Indexicality Metaphor

NL domains of application Internet

Information retrieval : search engines Information filtering: document grouping

Database Conclusion:

Current status Future trend

Introduction

What is Natural Query Language Interface? What is it for? Where would it be used?

Why do we need this interface? How much would it really help? Is it even possible?

Problems with implementation

• Ambiguity i.e. Semantics• Size of the language• Syntax And Grammars• Anaphora• Indexicality• Metaphor

Problems with implementation… Ambiguity and Semantics

The boy saw the man on the hill with the telescope

Ambiguity and Semantics What is wrong with this sentence? Ans:

Too ambiguous How many different meanings can it

have? The only way to truly understand is to be

there.

Ambiguity and Semantics

Another example of problems is with semantics.

The word up can have many meanings when used in different ways such as, “Look up there”, “It is up to me”, “Is he up to the task?”, “She is not up yet”, “Starting up”, “What’s up dude?”

More problems with implementation…

Size of the language

Most Natural Languages have enormous vocabulary.

Example: The English language has approximately 3 Million words, and counting. 200,000 of which are in common use today (and this isn’t counting semantics).

More problems with implementation…

Syntax And Grammars

Languages have alphabets and rules Sample alphabet {a, b} Sample (rewrite) rules:

S aSbS ba

This will generate words of type ba, abab, aababb, aaababbb

Syntax And Grammars…

English’s main constituents: Sentences Noun phrases Verb phrases Prepositional phrases

A sample English grammar S -> NP VP NP -> Det NOMINAL NOMINAL -> Noun VP -> Verb Det -> a Noun -> table Verb -> found

Any Problem with that grammar? It is context free grammar, it only

account for the syntactic structure. CFG works fine for any high level

language. How about the semantics of the

words?

Semantic Representations Can we create representations of

the meanings of the English words?.

This is not an easy task. It is a very complex task. A context sensitive grammar is

needed.

More problems with implementation…

Anaphora

What is Anaphora? Pronouns and Nouns

Why is it a problem? Key words have to be tallied.

How would it have to be Handled?

More problems with implementation… Indexicality

A sentence that refers to a situation (place or time)

Example: “I am over here” Where is “here”? Who is “I”?

More problems with implementation… Metaphor

Non literal use of a word. “This process was killed because it

ran out of resources” Meaning in manufacturing vs.

computers.

Domains of Application

Internet Information retrieval: with search

engines Information filtering: document

grouping More...

Database

NLIQ and the internet

Information retrieval: an English query is issued to a

search engine, Documents relevant to the query are returned.

Two methods are used

Exact matching Inexact matching

Exact Matching

restrictive and is known for low hits

Inexact Matching

higher hit rate …But User might have to scan a lot of

returned documents!!

How does it work?

select the ‘candidate key’ words from the query

‘a’, ‘the’, ‘an’ etc would not make it Count the key words in the

documents “running”, “run”, “ran” and

“runner” would count as one

How does it work…

Rank the documents by frequency of key words found

Information filtering

Documents are first prepared and then searched

Documents are ranked by topics

NLQI and Database

Database business, an industry that runs in the billions of dollars

a more user-friendly interface between the user and the machine is needed

NLQI seems to fit well

Example of DB use

Give me the names of the employees of Banks Of America who signed up for 401k?

Sounds easy? To humans, yes Not to machines!!

What does “up” mean?

Give me the names of the employees of Banks Of America who signed up for 401k?

Solution!

Create an index that has all the meanings of every word that can be used in database domain!!!

Then guess what “up” would mean

NLQI and Database…

Can’t use NLQI to create a database:

---Data integrity compromised Could use NLQI for information

retrieval: ---Performance compromised, to

say the least

Current status

NLQI is used in many areas today, but it is very (very) application specific. This is to avoid a lot of the problems discussed in this presentation.

Broad use and what NLQI is truly capable of has not yet been realized.

Future trend Where is it going? The trend is to store more and more

data per user to help determine exactly what semantics the user is really intending. This is called incremental enhancement of the data retrieval process

Will it ever get there?

Questions?

You’ve got questions, we’ve got answers

(hopefully).