add_word
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
add_word has 19 facts recorded in Dontopedia across 3 references, with 4 live disagreements.
Mostly:has parameter(4), rdf:type(3), takes parameter(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (3)
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.
hasMethodHas Method(2)
- Dictionary Lookup Class
ex:dictionary-lookup-class - Dictionarylookup Class
ex:dictionarylookup-class
callsCalls(1)
- Lookup Instance
ex:lookup-instance
Other facts (18)
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 |
|---|---|---|
| Has Parameter | word | [2] |
| Has Parameter | synonym | [2] |
| Has Parameter | word | [3] |
| Has Parameter | synonym | [3] |
| Rdf:type | Python Method | [1] |
| Rdf:type | Instance Method | [2] |
| Rdf:type | Python Method | [3] |
| Takes Parameter | word | [1] |
| Takes Parameter | synonym | [1] |
| Adds to | dictionary | [3] |
| Adds to | bloom-filter | [3] |
| Member of | Dictionary Lookup Class | [1] |
| Assigns Value | Empty Dictionary | [1] |
| Modifies State | Dictionary Lookup Class | [1] |
| Traverses | Word Characters | [2] |
| Creates | New Node | [2] |
| Sets | End of Word Flag | [2] |
| Assigns | Synonym Value | [2] |
Timeline
Timeline 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.
References (3)
ctx:claims/beam/1c58ca0d-e81e-449a-92f0-bddd6a966269- full textbeam-chunktext/plain1 KB
doc:beam/1c58ca0d-e81e-449a-92f0-bddd6a966269Show excerpt
[Turn 6892] User: I've found that dictionary lookups are causing latency spikes of up to 350ms for 15% of 6,000 queries. I need help optimizing the dictionary lookup process. Can you suggest a more efficient data structure or algorithm for …
ctx:claims/beam/eda34030-0bc4-4fab-bee6-4766ec39eee1- full textbeam-chunktext/plain1 KB
doc:beam/eda34030-0bc4-4fab-bee6-4766ec39eee1Show excerpt
1. **Use a Trie (Prefix Tree)**: If your dictionary contains words with common prefixes, a Trie can be more efficient for lookups. 2. **Hash Table with Custom Hash Function**: Ensure that the hash function is well-distributed to minimize co…
ctx:claims/beam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70a- full textbeam-chunktext/plain1 KB
doc:beam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70aShow excerpt
def __init__(self, expected_elements, false_positive_rate): self.dictionary = {} self.bloom_filter = BloomFilter(capacity=expected_elements, error_rate=false_positive_rate) def add_word(self, word, synonym): …
See also
Keep researching
Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.