Oct 19, 2020 · In this work, we introduce data augmentation techniques and a sampling-based content-aware BERT model (ColloQL) to achieve robust text-to-SQL ...
We introduce data augmentation techniques and a sampling-based content-aware BERT model (ColloQL) to achieve robust text-to-SQL modeling over natural language ...
Missing: Cross- | Show results with:Cross-
Translating natural language utterances to exe- cutable queries is a helpful technique in mak- ing the vast amount of data stored in relational.
This work introduces data augmentation techniques and a sampling-based content-aware BERT model (ColloQL) to achieve robust text-to-SQL modeling over ...
Contains code and data from our upcoming EMNLP workshop paper "ColloQL: Robust Cross-Domain Text-to-SQL Over Search Queries". Largely adapted from SQLova ...
Robust semantic parsing techniques [7, 94] may also help with interpreting illspecified user queries. ...
Oct 19, 2020 · In this work, we introduce data augmentation techniques and a sampling-based content-aware BERT model (ColloQL) to achieve robust text-to-SQL ...
Oct 19, 2020 · In this work, we introduce data augmentation techniques and a sampling-based content-aware BERT model (ColloQL) to achieve robust text-to-SQL ...
Text-to-SQL is a task in natural language processing (NLP) where the goal is to automatically generate SQL queries from natural language text.
PHOTON is presented, a robust, modular, cross-domain NLIDB that can flag natural language input to which a SQL mapping cannot be immediately determined and ...