Towards Natural Language Question Answering over Earth Observation Linked Data using Attention-based Neural Machine Translation

01/23/2021
by   Abhishek V. Potnis, et al.
0

With an increase in Geospatial Linked Open Data being adopted and published over the web, there is a need to develop intuitive interfaces and systems for seamless and efficient exploratory analysis of such rich heterogeneous multi-modal datasets. This work is geared towards improving the exploration process of Earth Observation (EO) Linked Data by developing a natural language interface to facilitate querying. Questions asked over Earth Observation Linked Data have an inherent spatio-temporal dimension and can be represented using GeoSPARQL. This paper seeks to study and analyze the use of RNN-based neural machine translation with attention for transforming natural language questions into GeoSPARQL queries. Specifically, it aims to assess the feasibility of a neural approach for identifying and mapping spatial predicates in natural language to GeoSPARQL's topology vocabulary extension including - Egenhofer and RCC8 relations. The queries can then be executed over a triple store to yield answers for the natural language questions. A dataset consisting of mappings from natural language questions to GeoSPARQL queries over the Corine Land Cover(CLC) Linked Data has been created to train and validate the deep neural network. From our experiments, it is evident that neural machine translation with attention is a promising approach for the task of translating spatial predicates in natural language questions to GeoSPARQL queries.

READ FULL TEXT
research
11/04/2021

Reducing the impact of out of vocabulary words in the translation of natural language questions into SPARQL queries

Accessing the large volumes of information available in public knowledge...
research
07/14/2020

Template-Based Question Answering over Linked Geospatial Data

Large amounts of geospatial data have been made available recently on th...
research
06/21/2019

Neural Machine Translating from Natural Language to SPARQL

SPARQL is a highly powerful query language for an ever-growing number of...
research
06/27/2018

Neural Machine Translation for Query Construction and Composition

Research on question answering with knowledge base has recently seen an ...
research
08/25/2017

SPARQL as a Foreign Language

In the last years, the Linked Data Cloud has achieved a size of more tha...
research
10/21/2020

Exploring Sequence-to-Sequence Models for SPARQL Pattern Composition

A booming amount of information is continuously added to the Internet as...
research
07/14/2018

Generating Synthetic Data for Neural Keyword-to-Question Models

Search typically relies on keyword queries, but these are often semantic...

Please sign up or login with your details

Forgot password? Click here to reset