<jupyter_start><jupyter_text>What drugs/compounds target gene products of gene "coagulation factor II, thrombin"Built from https://github.com/paulovn/sparql-kernel/tree/master/examples<jupyter_code>%endpoint http://dbpedia.org/sparql
%lang en

# This is optional, it would increase the log level.
# The default logfile (unless changed upon kernel installation) is [TMPDIR]/sparqlkernel.log, 
# where [TMPDIR] is the platform default temporal directory
%log debug
%format JSON
%display table

PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX foaf:  <http://xmlns.com/foaf/0.1/>
SELECT ?person ?name
WHERE {
    ?person a foaf:Person .
    ?person rdfs:label ?name
    FILTER regex(?name,"van gogh","i")
    FILTER langMatches(lang(?name),"en")
} LIMIT 20<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12468513853904283, 'fraction_numerical': 0.013853904282115869, 'mean_word_length': 5.068702290076335, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 7, 'https://': 1, 'lorem ipsum': 0, 'www.': 1, 'xml': 1}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '407128', 'license': 'MIT', 'n_tokens_mistral': 287, 'n_tokens_neox': 270, 'n_words': 72, 'path': 'sparql-kernel.ipynb', 'repo_name': 'vemonet/translator-sparql-notebook', 'size': '794'}