Ashish Palakurthi

  • Citations Per Year
Learn More
This paper proposes a novel approach to capture the concept<sup>1</sup> of an NL query. Given an NL query, the query is mapped to a tagset, which carries the concepts information. The tagset was created by mapping every noun chunk to the attribute of a table (tableName.attributeNarne) and every verb chunk to a relation in the ER schema. The approach is(More)
This paper describes the system that was submitted to SemEval2016 Task 11: Complex Word Identification. It presents a preliminary investigation into exploring word difficulty for non-native English speakers. We developed two systems using Nearest Centroid Classification technique to distinguish complex words from simple words. Optimized over G-score, the(More)
Attribute information in a natural language query is one of the key features for converting a natural language query into a Structured Query Language1 (SQL) in Natural Language Interface to Database systems. In this paper, we explore the task of classifying the attributes present in a natural language query into different SQL clauses in a SQL query. In(More)
In this paper we explain the identification of karaka relations in an English sentence. We explain the genesis of the problem and present two different approaches, rule based and statistical. We briefly describe about rule based and focus more on statistical approach. We process a sentence through various stages and extract features at each stage. We train(More)
Natural Language Interface to Database (NLIDB) systems convert a Natural Language (NL) query into a Structured Query Language (SQL) and then use the SQL query to retrieve information from a database. The main advantage with this function of an NLIDB system is that it makes information retrieval much easier and more importantly, it also allows non-technical(More)
  • 1