  The Natural Language Processing (NLP) community has significantly contributed
to the solutions for entity and relation recognition from the text, and
possibly linking them to proper matches in Knowledge Graphs (KGs). Considering
Wikidata as the background KG, still, there are limited tools to link knowledge
within the text to Wikidata. In this paper, we present Falcon 2.0, first joint
entity, and relation linking tool over Wikidata. It receives a short natural
language text in the English language and outputs a ranked list of entities and
relations annotated with the proper candidates in Wikidata. The candidates are
represented by their Internationalized Resource Identifier (IRI) in Wikidata.
Falcon 2.0 resorts to the English language model for the recognition task
(e.g., N-Gram tiling and N-Gram splitting), and then an optimization approach
for linking task. We have empirically studied the performance of Falcon 2.0 on
Wikidata and concluded that it outperforms all the existing baselines. Falcon
2.0 is public and can be reused by the community; all the required instructions
of Falcon 2.0 are well-documented at our GitHub repository. We also demonstrate
an online API, which can be run without any technical expertise. Falcon 2.0 and
its background knowledge bases are available as resources at
https://labs.tib.eu/falcon/falcon2/.
