Related papers: Enriching Wikidata with Linked Open Data
Scientists always look for the most accurate and relevant answers to their queries in the literature. Traditional scholarly digital libraries list documents in search results, and therefore are unable to provide precise answers to search…
Online encyclopedia such as Wikipedia has become one of the best sources of knowledge. Much effort has been devoted to expanding and enriching the structured data by automatic information extraction from unstructured text in Wikipedia.…
Applications of large open-domain knowledge graphs (KGs) to real-world problems pose many unique challenges. In this paper, we present extensions to Saga our platform for continuous construction and serving of knowledge at scale. In…
The last 30 years have seen the creation of a variety of electronic collaboration tools for science and business. Some of the best-known collaboration tools support text editing (e.g., wikis). Wikipedia's success shows that large-scale…
The Big Data landscape poses challenges in managing diverse data formats, requiring efficient storage and processing for high-quality analysis. Effective metadata management is crucial for organizing, accessing, and reusing data within…
While the potential of Open Information Extraction (Open IE) for Knowledge Graph Construction (KGC) may seem promising, we find that the alignment of Open IE extraction results with existing knowledge graphs to be inadequate. The advent of…
With the growth of fake news and disinformation, the NLP community has been working to assist humans in fact-checking. However, most academic research has focused on model accuracy without paying attention to resource efficiency, which is…
Answering complex questions over textual resources remains a challenge, particularly when dealing with nuanced relationships between multiple entities expressed within natural-language sentences. To this end, curated knowledge bases (KBs)…
With the development of the Semantic Web technology, the use of ontologies to store and retrieve information covering several domains has increased. However, very few ontologies are able to cope with the ever-growing need of frequently…
Hyperlinks and other relations in Wikipedia are a extraordinary resource which is still not fully understood. In this paper we study the different types of links in Wikipedia, and contrast the use of the full graph with respect to just…
Knowledge graphs (KGs) have become ubiquitous publicly available knowledge sources, and are nowadays covering an ever increasing array of domains. However, not all knowledge represented is useful or pertaining when considering a new…
The term Data Space, understood as the secure exchange of data in distributed systems, ensuring openness, transparency, decentralization, sovereignty, and interoperability of information, has gained importance during the last years.…
Wikipedia is a huge opportunity for machine learning, being the largest semi-structured base of knowledge available. Because of this, many works examine its contents, and focus on structuring it in order to make it usable in learning tasks,…
Knowledge graphs are an efficient method for representing and connecting information across various concepts, useful in reasoning, question answering, and knowledge base completion tasks. They organize data by linking points, enabling…
Abstract- The vision of the Linked Open Data (LOD) initiative is to provide a distributed model for publishing and meaningfully interlinking open data. The realization of this goal depends strongly on the quality of the data that is…
We present a Wikidata-based framework, called KIF, for virtually integrating heterogeneous knowledge sources. KIF is written in Python and is released as open-source. It leverages Wikidata's data model and vocabulary plus user-defined…
Linked Open Datasets about scholarly publications enable the development and integration of sophisticated end-user services; however, richer datasets are still needed. The first goal of this Challenge was to investigate novel approaches to…
Data verbalisation is a task of great importance in the current field of natural language processing, as there is great benefit in the transformation of our abundant structured and semi-structured data into human-readable formats.…
Public knowledge graphs such as DBpedia and Wikidata have been recognized as interesting sources of background knowledge to build content-based recommender systems. They can be used to add information about the items to be recommended and…
Software repositories contain valuable information for understanding the development process. However, extracting insights from repository data is time-consuming and requires technical expertise. While software engineering chatbots support…