DBpedia

AbstractOne of the objectives of the Language Technologies for Life-Long Learning (LTfLL) project, is to develop a knowledge sharing system that connects learners to resources and learners to other learners. …...

s Jared Willett,♠ Timothy Baldwin,♠♥ David Martinez♥ and Angus Webb♦ ♠ Department of Computing and Information Systems ♥ NICTA Victoria Research Laboratory ♦ Department of Resource Management and Geography The …...

AbstractThe DBpedia project extracts structured information from Wikipedia editions in 97 different languages and combines this information into a large multi-lingual knowledge base covering many specific domains and general world …...

AbstractEnterprise content analysis and platform configuration for enterprise content management is often carried out by external consultants that are not necessarily domain experts. In this paper, we propose a set …...

Sentiment Analysis in Twitter has become an important task due to the huge user-generated content published over such media. Such analysis could be useful for many domains such as Marketing, …...

AbstractNamed entity recognition and disambiguation are of primary importance for extracting information and for populating knowledge bases. Detecting and classifying named entities has traditionally been taken on by the natural …...

AbstractIn this paper we present CROMER (CROss-document Main Events and entities Recognition), a novel tool to manually annotate event and entity coreference across clusters of documents. The tool has been …...

AbstractWe present an approach for augmenting DBpedia, a very large ontology lying at the heart of the Linked Open Data (LOD) cloud, with domain information. Our approach uses the thematic …...

Much work in recent years has gone into the construction of large knowledge bases (KBs), such as Freebase, DBPedia, NELL, and YAGO. While these KBs are very large, they are …...

AbstractThis research provides a comparison of a linked open data resource (DBpedia) and web corpus data resources (Google Web Ngrams and Google Books Ngrams) for noun compound bracketing. Large corpus …...

AbstractIn recent years large repositories of structured knowledge (DBpedia, Freebase, YAGO) have become a valuable resource for language technologies, especially for the automatic aggregation of knowledge from textual data. One …...

AbstractThis paper presents a statistical type inference algorithm for ontology alignment, which assigns DBpedia entities with a new type (class). To infer types for a specific entity, the algorithm first …...

We present WiBi, an approach to the automatic creation of a bitaxonomy for Wikipedia, that is, an integrated taxon- omy of Wikipage pages and categories. We leverage the information available …...

Our goal is to facilitate named en- tity recognition in Bulgarian texts by extending the coverage of DBpedia (http://www.dbpedia.org/) for Bul- garian. For this task we have trained translation Moses …...

Some state-of-the-art summarization systems use integer linear programming (ILP) based methods that aim to maximize the important concepts covered in the summary. These con- cepts are often obtained by selecting …...

AbstractNamed Entity Disambiguation (NED) is the task of linking a named-entity mention to an instance in a knowledge-base, typically Wikipedia-derived resources like DBpedia. This task is closely related to word-sense …...

AbstractIn order to make the growing amount of conceptual knowledge available through ontologies and datasets accessible to humans, NLP applications need access to information on how this knowledge can be …...

AbstractOntologies are powerful to support semantic based applications and intelligent systems. While ontology learning are challenging due to its bottleneck in handcrafting structured knowledge sources and training data. To address …...

A difficult task when generating text from knowledge bases (KB) consists in finding appropriate lexicalisations for KB sym- bols. We present an approach for lexicalis- ing knowledge base relations and …...

AbstractIn this paper, we present a novel framework for semi-automatically creating linguistically challenging micro-planning data-to-text corpora from existing Knowledge Bases. Because our method pairs data of varying size and shape …...

This paper presents a multi-domain interests dataset to train and test Recommender Systems, and the methodology to create the dataset from Twitter messages in English and Italian. The English dataset …...

AbstractWe propose an unsupervised approach for assessing conceptual complexity of texts, based on spreading activation. Using DBpedia knowledge graph as a proxy to long-term memory, mentioned concepts become activated and …...

AbstractWe present MKGDB, a large-scale graph database created as a combination of multiple taxonomy backbones extracted from 5 existing knowledge graphs, namely: ConceptNet, DBpedia, WebIsAGraph, WordNet and the Wikipedia category …...

AbstractFine-tuning with pre-trained language models (e.g. BERT) has achieved great success in many language understanding tasks in supervised settings (e.g. text classification). However, relatively little work has been focused on …...

AbstractIn recent years the interest in the use of repositories of literary works has been successful. While many efforts related to Linked Open Data go in the right direction, the …...

AbstractLarge-scale pretrained language models have led to significant improvements in Natural Language Processing. Unfortunately, they come at the cost of high computational and storage requirements that complicate their deployment on …...

AbstractPredicting missing facts in a knowledge graph (KG) is crucial as modern KGs are far from complete. Due to labor-intensive human labeling, this phenomenon deteriorates when handling knowledge represented in …...

AbstractPretrained language models (PLMs) for data-to-text (D2T) generation can use human-readable data labels such as column headings, keys, or relation names to generalize to out-of-domain examples. However, the models are …...

AbstractThe WebNLG task consists of mapping a knowledge graph to a text verbalising the con- tent of that graph. The 2017 WebNLG edi- tion required participating systems to gener- ate …...