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LiberAI / gsoc

Liber AI's application for the Google Summer of Code.
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[GSoC 2022] Template Discovery for Neural SPARQL Machines #1

Closed mommi84 closed 2 years ago

mommi84 commented 2 years ago

This project started in 2018 and is now looking to its 5th consecutive year at Google Summer of Code.

Introduction

Neural SPARQL Machines (NSpM) aim at building an end-to-end system to answer questions posed by user not versed with writing SPARQL queries.

Currently, billions of relationships on the Web are expressed in the RDF format. Accessing such data is difficult for a lay user, who does not know how to write a SPARQL query. This GSoC project consists of building upon the NSpM question answering system, which tries to make this humongous linked data accessible to a larger user base in their natural language (as of now restricted to English) by improving, adding and amending upon the existing codebase.

Documentation

Reading Material

The first 3 papers introduce and elaborate on Neural SPARQL Machines. Work number 3 was carried out by our GSoC 2019 student and published at KGSWC 2020. The 4th paper is an almost-complete survey of related approaches.

  1. SPARQL as a Foreign Language: https://arxiv.org/abs/1708.07624
  2. Neural Machine Translation for Query Construction and Composition: https://arxiv.org/abs/1806.10478
  3. Exploring Sequence-to-Sequence Models for SPARQL Pattern Composition: https://arxiv.org/abs/2010.10900
  4. Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs: https://arxiv.org/pdf/1907.09361.pdf

GSoC Blogs

You may also check which problems past GSoC contributors worked on:

  1. [GSoC 2018 at DBpedia] Aman's Blog: https://amanmehta-maniac.github.io/
  2. [GSoC 2019 at DBpedia] Anand's Blog: https://anandpanchbhai.com/A-Neural-QA-Model-for-DBpedia/
  3. [GSoC 2020 at DBpedia] Zheyuan's Blog: https://baiblanc.github.io/
  4. [GSoC 2021 at DBpedia] Siddhant's Blog: https://imsiddhant07.github.io/Neural-QA-Model-for-DBpedia/

Warm-up tasks

  1. Read through the blogs and the reading list to get a good understanding of the code. This will allow you to get a good idea about the project.
  2. Run the pipelines in the ./gsoc/anand and ./gsoc/zheyuan folders of the base repository using examples of your choice.

Your proposal

Now that you have a good understanding of the current state of the project, we suggest you to build proposals pondering on some of the following points, feel free to bring your own solutions to tackle the problems that the project faces.

  1. How can we automatically build the right question from the property label only?
    • example a) from <s> dbo:birthPlace <o> infer where was <s> born?
    • example b) from <s> dbo:timeZone <o> infer what time zone is <s> in?
  2. How can we automatically build question-query templates that feature one or more of the following?
    • subordinate clauses or genitive: which / that / of / ’s
    • con-/disjunctions: and / or / as well as
    • modifiers: which + mod / what + mod / demonyms
    • comparative: more than / -er than
    • superlative: most … / -est
    • numeric / quantitative: how many / long / tall

Consider experimenting with advanced approaches such as:

Additional information

Mentors

@mommi84, @panchbhai1969, TBD

Feel free to contact us for more information. We eagerly look forward to working with you and contributing towards making data accessible to all.

mommi84 commented 2 years ago

Liber AI was not accepted to GSoC 2022, however contributors may still apply via DBpedia at the following link: