Search Results for author:
Found 14 papers, 8 papers with code
GraLMatch: Matching Groups of Entities with Graphs and Language Models
In this paper, we present an end-to-end multi-source Entity Matching problem, which we call entity group matching, where the goal is to assign to the same group, records originating from multiple data sources but representing the same real-world entity.
StatBot.Swiss: Bilingual Open Data Exploration in Natural Language
The potential for improvements brought by Large Language Models (LLMs) in Text-to-SQL systems is mostly assessed on monolingual English datasets.
Evaluating the Data Model Robustness of Text-to-SQL Systems Based on Real User Queries
All of our data is based on real user questions that were asked live to the system.
Spider4SPARQL: A Complex Benchmark for Evaluating Knowledge Graph Question Answering Systems
With the recent spike in the number and availability of Large Language Models (LLMs), it has become increasingly important to provide large and realistic benchmarks for evaluating Knowledge Graph Question Answering (KGQA) systems.
Data-Driven Information Extraction and Enrichment of Molecular Profiling Data for Cancer Cell Lines
This system extracts deep semantic relations between textual entities from scientific literature to enrich existing structured clinical data in the domain of cancer cell lines.
ScienceBenchmark: A Complex Real-World Benchmark for Evaluating Natural Language to SQL Systems
Thus, the challenge is many-fold: creating NL-to-SQL systems for highly complex domains with a small amount of hand-made training data augmented with synthetic data.
Multiple Query Optimization using a Hybrid Approach of Classical and Quantum Computing
Our experimental results demonstrate that our algorithm currently can only handle small problem sizes due to the limited number of qubits available on a gate-based quantum computer compared to a quantum computer based on quantum annealing.
INODE: Building an End-to-End Data Exploration System in Practice [Extended Vision]
We demonstrate that our system is uniquely accessible to a wide range of users from larger scientific communities to the public.
ValueNet: A Natural Language-to-SQL System that Learns from Database Information
In this paper we propose ValueNet light and ValueNet -- two end-to-end NL-to-SQL systems that incorporate values using the challenging Spider dataset.
Database Search vs. Information Retrieval: A Novel Method for Studying Natural Language Querying of Semi-Structured Data
In this paper, we provide an adapted benchmark data set that is based on a test collection originally used to evaluate information retrieval systems.
A Methodology for Creating Question Answering Corpora Using Inverse Data Annotation
For this, we introduce an intermediate representation that is based on the logical query plan in a database called Operation Trees (OT).
Join Query Optimization with Deep Reinforcement Learning Algorithms
The main idea of FOOP is to use a data-adaptive learning query optimizer that avoids exhaustive enumerations of join orders and is thus significantly faster than traditional approaches based on dynamic programming.
A Comparative Survey of Recent Natural Language Interfaces for Databases
Each of the systems is evaluated using a curated list of ten sample questions to show their strengths and weaknesses.
VoIDext: Vocabulary and Patterns for Enhancing Interoperable Datasets with Virtual Links
Semantic heterogeneity remains a problem when interoperating with data from sources of different scopes and knowledge domains.
