WannaDB: Ad-hoc SQL Queries over Text Collections

Abstract

In this paper, we propose a new system called WannaDB that allows users to interactively perform structured explorations of text collections in an ad-hoc manner. Extracting structured data from text is a classical problem where a plenitude of approaches and even industry-scale systems already exists. However, these approaches lack in the ability to support the ad-hoc exploration of texts using structured queries. The main idea of WannaDB is to include user interaction to support ad-hoc SQL queries over text collections using a new two-phased approach. First, a superset of information nuggets from the texts is extracted using existing extractors such as named entity recognizers. Then, the extractions are interactively matched to a structured table definition as requested by the user based on embeddings. In our evaluation, we show that WannaDB is thus able to extract structured data from a broad range of (real-world) text collections in high quality without the need to design extraction pipelines upfront