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Processed Tokens has 23 facts recorded in Dontopedia across 10 references, with 3 live disagreements.
Mostly:rdf:type(9), rdfs:label(4), initialized as(2)
rdfs:labelinitializedAsaccumulatesisAccumulatorForassignedFromaccumulatesValidTokensis-populatedByresultOfvariableTypereassignedOther subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. “X motherOf this subject” — and answer questions the forward facts can't. Grouped by predicate.
returnsReturns(5)ex:parse_queryex:parse_query_functionex:preprocess_queryex:processex:token-processing-functionappendsToAppends to(2)ex:skip_empty_tokensex:token-processing-functionallSpecialCharactersCheckAll Special Characters Check(1)ex:parse_queryappendsToVariableAppends to Variable(1)ex:parse_queryhasVariableHas Variable(1)ex:parse_queryiteratesIterates(1)ex:lemmatization_stepprintsPrints(1)ex:example_usagereturnsVariableReturns Variable(1)ex:parse_querysourceCollectionSource Collection(1)ex:list_comp_lemmatizationtargetObjectTarget Object(1)ex:list_appendTimeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
doc:beam/208145c7-d56c-489b-85d2-484dde96b52cprint(f"Processed: {parse_query(query)}") ``` ### Explanation 1. **Empty Query Check**: - `if not query.strip(): return []`: Returns an empty list if the query is empty or contains only whitespace. 2. **Tokenization**: - `token…
doc:beam/1662e889-1d00-4c4a-b8fc-a7b792ed07e3import concurrent.futures def parse_query(query): # Tokenize the query tokens = re.split(r'\s+', query) # Adjust token boundaries and remove special characters in one pass processed_tokens = [] for token in tokens:…
doc:beam/200959f7-7b94-4238-988c-0b57fc083432```python import re def parse_query(query): # Check for empty query if not query.strip(): return [] # Tokenize the query tokens = re.split(r'\s+', query) # Process the tokens processed_tokens = [] …
doc:beam/7032b876-1fd3-45e3-9cf6-5ab1c78bd4dc# Remove special characters token = re.sub(r'[^a-zA-Z0-9]', '', token) processed_tokens.append(token) return processed_tokens # Test the function queries = ["This is a test query", "Another query with speci…
doc:beam/e50e1439-fa74-447d-ba48-a7a4b6694859cleaned_text = re.sub(r"(\bcan't\b)", "cannot", cleaned_text) return cleaned_text def detect_language(text): try: lang = langdetect.detect(text) return lang except langdetect.LangDetectException: ret…
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