自然语言处理数据库查询

Question

I need to develop natural language querying tool for a structured database. I tried two approaches.

• using Python nltk (Natural Language Toolkit for python) using
• Javascript and JSON (for data source)

In the first case I did some NLP steps to format the natural query by doing removing stop words, stemming, finally mapping keywords using featured grammar mapping. This methodology works for simple scenarios.

Then I moved to second approach. Finding the data in JSON and getting corresponding column name and table name , then building a sql query. For this one, I also implemented removing stop words, stemming using javascript.

Both of these techniques have limitations.I want to implement semantic search approach.

Please can anyone suggest me better approach to do this..

Answer 1

Semantic parsing for NLIDB (natural language interface to data bases) is a very evolved domain with many techniques: rule based methods (involving grammars) or machine learning techniques. They cover a large range of query inputs, and offer much more results than pure NL processing or regex methods.

The technique I favor is based on Feature based context-free grammars FCFG . For starters, in the NTLK book available online , look for the string "sql0.fcfg". The code example shows how to map the NL phrase structure query "What cities are located in China" into an SQL query "SELECT City FROM city_table WHERE Country="china" via the feature "SEM" or semantics of the FCFG.

I recommend Covington's books

• NLP for Prloog Programmers (1994)
• Prolog Programming in Depth (1997)

They will help You go a long way. These PDF's are downloadable from his site .

Answer 2

As I commented, I think you should add some code, since not everyone has read the book.

Anyway my conclusion is that yes, as you said it has a lot of limitations and the only way to achieve more complex queries is to write very extensive and complete grammar productions, a pretty hard work.