rewritten_tokens
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
rewritten_tokens is a new list of tokens for replacements.
Mostly:rdf:type(4), description(1), purpose(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (4)
Other 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.
appendsToAppends to(2)
- Append Original Token
ex:append-original-token - Append Replacement
ex:append-replacement
createsVariableCreates Variable(1)
- Build Rewritten Tokens
ex:build-rewritten-tokens
sourceSource(1)
- String Construction
ex:string-construction
Other facts (10)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Variable | [1] |
| Rdf:type | Token List | [2] |
| Rdf:type | Array | [3] |
| Rdf:type | Variable | [4] |
| Description | a new list of tokens for replacements | [2] |
| Purpose | avoids overhead of repeated string manipulations | [2] |
| Constructed by | list-comprehension | [3] |
| Source of | Rewritten Query | [3] |
| Variable Name | rewritten_tokens | [4] |
| Initialized From | list-comprehension | [4] |
Timeline
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References (4)
ctx:claims/beam/0d14207a-c30c-42b6-a866-e778dbb3ec81ctx:claims/beam/a085a169-aa15-4448-83bc-ecb888dadb5c- full textbeam-chunktext/plain1 KB
doc:beam/a085a169-aa15-4448-83bc-ecb888dadb5cShow excerpt
- Instead of repeatedly replacing tokens in the original string, we build a new list of tokens (`rewritten_tokens`) with the replacements. - This avoids the overhead of repeated string manipulations. 2. **Set for Quick Lookups**: …
ctx:claims/beam/819c8d1c-ceee-4ed2-8fa3-23504b8df714- full textbeam-chunktext/plain964 B
doc:beam/819c8d1c-ceee-4ed2-8fa3-23504b8df714Show excerpt
dictionary_keys = set(dictionary.keys()) rewritten_queries = [] for query in queries: tokens = query.split() rewritten_tokens = [dictionary[token] if token in dictionary_keys else token for token in tokens] …
ctx:claims/beam/d55a690a-9cf4-4df0-804c-785499773a30- full textbeam-chunktext/plain1 KB
doc:beam/d55a690a-9cf4-4df0-804c-785499773a30Show excerpt
- If the dataset is large, consider using parallel processing techniques to distribute the workload across multiple cores or processes. ### Example with Batch Processing If you are processing multiple queries, you can batch them togeth…
See also
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