As a result, WordNet has enabled a wide variety of NLP techniques such as Word Sense Disambiguation (Agirre et al., 2014), information retrieval (Varelas et al., 2005), semantic similarity (Pedersen et al., 2004;Bär et al., 2013), and sentiment analysis (Baccianella et al., 2010).
semantic knowledge bases such as WordNet are expensive to produce; as a result, their scope and domain are often constrained by the resources available and may omit highly-specific concepts or lemmas, as well as new terminology that emerges after their construction.