<jupyter_start><jupyter_text>Lesk in NLTK<jupyter_code>import nltk
nltk.download('wordnet')
context = ['I', 'went', 'to', 'the', 'bank', 'to', 'deposit', 'money', '.']

synset = nltk.wsd.lesk(context, 'bank', 'n')

synset
synset.definition()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.2177121771217712, 'fraction_numerical': 0.0, 'mean_word_length': 8.066666666666666, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '176067', 'license': 'MIT', 'n_tokens_mistral': 122, 'n_tokens_neox': 119, 'n_words': 20, 'path': 's6/codes/s6a.ipynb', 'repo_name': 'gebakx/ihlt', 'size': '271'}