Diachronic Analysis of Entities by Exploiting Wikipedia Page revisions
In the last few years, the increasing availability of large corpora spanning several time periods has opened new opportunities for the diachronic analysis of language. This type of analysis can bring to the light not only linguistic phenomena related to the shift of word meanings over time, but it can also be used to study the impact that societal and cultural trends have on this language change. This paper introduces a new resource for performing the diachronic analysis of named entities built upon Wikipedia page revisions. This resource enables the analysis over time of changes in the relations between entities (concepts), surface forms (words), and the contexts surrounding entities and surface forms, by analysing the whole history of Wikipedia internal links. We provide some useful use cases that prove the impact of this resource on diachronic studies and delineate some possible future usage.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
How much is Wikipedia Lagging Behind News?
Wikipedia, rich in entities and events, is an invaluable resource for various knowledge harvesting, extraction and mining tasks. Numerous resources like DBpedia, YAGO and other knowledge bases are based on extracting ent…
ArticlesKEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness
In recent years, Pre-trained Language Models (PLMs) have shown their superiority by pre-training on unstructured text corpus and then fine-tuning on downstream tasks. On entity-rich textual resources like Wikipedia, Know…
Entity LinkingLanguage ModelingLanguage ModellingRelation+2Entity Extraction from Wikipedia List Pages
When it comes to factual knowledge about a wide range of domains, Wikipedia is often the prime source of information on the web. DBpedia and YAGO, as large cross-domain knowledge graphs, encode a subset of that knowledge…
Entity Extraction using GANKnowledge GraphsSemantic Annotation for Microblog Topics Using Wikipedia Temporal Information
Trending topics in microblogs such as Twitter are valuable resources to understand social aspects of real-world events. To enable deep analyses of such trends, semantic annotation is an effective approach; yet the proble…
Entity Linking with people entity on Wikipedia
This paper introduces a new model that uses named entity recognition, coreference resolution, and entity linking techniques, to approach the task of linking people entities on Wikipedia people pages to their correspondin…
coreference-resolutionCoreference ResolutionEntity Linkingnamed-entity-recognition+2