Closed MarianoRico closed 4 years ago
Hi Mariano. I think this is a good idea but something is not clear for me. Is the impact only increasing the number of triples or is it also improving the tool? Because if it is the first case @chile12 and I developed a tool for Springer Nature abstracts (for this project: https://github.com/dbpedia/sci-graph-links) which can be also used for DBpedia abstracts as well. Besides, as an option I would suggest to integrate some other performance tools to this idea which might be quite interesting (e.g., https://eprints.weblyzard.com/112/2/Odoni_Kuntschik_Brasoveanu_Weichselbraun_semantics2018_orbis_cr.pdf )
Well, we can use the tools you mention as "warm up" tasks. Do you have some paper describing the sci-graph-links tool?
Here is the tool: https://github.com/beyzayaman/NER-assessment-for-springer-nature-abstracts But there is no further documentation about it except on the page. In case it is necessary I might try to prepare some.
Hi Marino, I am interested in taking up this project up. I have a good understanding in Natural Language processing including POS tagging and Entity extraction. I am familiar with the use and how SyntaxNet works. How can I proceed towards this project?
Hello Mariano, I find this project very interesting (and in fact similar to a pet project that I am working on) I have experience with RDFs, SyntaxNet and other parsers. I also know the procedure of converting the parse tree to RDF triples. I would be delighted to work on this project. Regards, Aditya Malte (P.S. I've sent you a mail detailing my approach)
Hi Mariano. Very interesting project. I'm a student in a Master in Artificial Intelligence and I'm very interested in natural language processing and open source. I'll apply for sure.
Description
With the recent advances (e.g. SyntaxNet) in the analysis of texts in natural language, the conversion of texts into RDF triples is becoming a real possibility. This project will apply these ideas to a real use case: DBpedia. We will add the power of syntactic analyzers with the benefits of Name Entity identifiers (like Spotlight) to generate highly trustable RDF triples from the textual information (long abstract) about a given DBpedia resource.
Goals
The tool created will generate a new nt file with the triples proposed for all the DBpedia resources. This tools could be exploited by the DBpedia extraction process to provide a new nt file in the DBpedia downloads.
Impact
Increase the number of RDF triples for a given DBpedia resource.
Warm up tasks
Experience with SyntaxNet o any other NLP tool capable of providing a syntactic analyzer of natural language. Here we have to reach a balance between power and number of supported languages. Fluent RDF and DBpedia datasets (downloads).
Mentors
Mariano Rico
Keywords
NLP, text parsing, syntactic analysis, RDF generation