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Named Entity Recognition and Disambiguation (NERD) systems are foundationalfor information retrieval, question answering, event detection, and othernatural language processing (NLP) applications. We introduce TweetNERD, adataset of 340K+ Tweets across 2010-2021, for benchmarking NERD systems onTweets. This is the largest and most temporally diverse open sourced datasetbenchmark for NERD on Tweets and can be used to facilitate research in thisarea. We describe evaluation setup with TweetNERD for three NERD tasks: NamedEntity Recognition (NER), Entity Linking with True Spans (EL), and End to EndEntity Linking (End2End); and provide performance of existing publiclyavailable methods on specific TweetNERD splits. TweetNERD is available at:https://doi.org/10.5281/zenodo.6617192 under Creative Commons Attribution 4.0International (CC BY 4.0) license. Check out more details athttps://github.com/twitter-research/TweetNERD.

TweetNERD -- End to End Entity Linking Benchmark for Tweets