Similarity Scores
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Similarity Scores has 11 facts recorded in Dontopedia across 3 references, with 3 live disagreements.
Mostly:computed from(4), rdf:type(2), relates(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedComputed Fromin disputecomputedFrom
- Passage Embeddings[1]sourceall time · Af659f61 D237 4091 A8b5 4a63d8ff2fae
- Query Embeddings[1]sourceall time · Af659f61 D237 4091 A8b5 4a63d8ff2fae
- Query Vector[2]sourceall time · 7780940c 0855 4439 B672 6739b7459e87
- Tfidf Matrix[2]sourceall time · 7780940c 0855 4439 B672 6739b7459e87
Rdf:typein disputerdf:type
Relatesin disputerelates
Target ValuetargetValue
- 1[1]all time · Af659f61 D237 4091 A8b5 4a63d8ff2fae
Measuresmeasures
- Query Document Similarity[3]sourceall time · 9016225f E83c 48c0 90be 7022b351ca10
Computed UsingcomputedUsing
- Tf Idf Matrix[3]sourceall time · 9016225f E83c 48c0 90be 7022b351ca10
Inbound mentions (14)
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.
computesComputes(3)
- Get Synonyms Function
ex:get-synonyms-function - Search Operation
ex:search-operation - Similarity Scoring
ex:similarity-scoring
returnsReturns(2)
- Cosine Similarity
ex:cosine-similarity - Sparse Retrieval Function
ex:sparse-retrieval-function
computedFromComputed From(1)
- Loss
ex:loss
expectedOutputExpected Output(1)
- Dense Retrieval Function
ex:dense-retrieval-function
isUsedForIs Used for(1)
- Tf Idf Matrix
ex:tf-idf-matrix
maximizesMaximizes(1)
- Training Objective
ex:training-objective
subtractsOneFromSubtracts One From(1)
- Loss Formula Component
ex:loss-formula-component
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)
- custom
ctx:claims/beam/af659f61-d237-4091-a8b5-4a63d8ff2fae- full textbeam-chunktext/plain1 KB
doc:beam/af659f61-d237-4091-a8b5-4a63d8ff2faeShow excerpt
query_embeddings = model(**query_encodings)['last_hidden_state'][:, 0, :] passage_embeddings = model(**passage_encodings)['last_hidden_state'][:, 0, :] # Apply dropout query_embeddings = dropout(query_embedd…
- custom
ctx:claims/beam/7780940c-0855-4439-b672-6739b7459e87- full textbeam-chunktext/plain1 KB
doc:beam/7780940c-0855-4439-b672-6739b7459e87Show excerpt
url = 'https://api-free.deepl.com/v2/translate' data = { 'auth_key': api_key, 'text': text, 'target_lang': target_lang } response = requests.post(url, data=data) return response.js…
- custom
ctx:claims/beam/9016225f-e83c-48c0-90be-7022b351ca10- full textbeam-chunktext/plain951 B
doc:beam/9016225f-e83c-48c0-90be-7022b351ca10Show excerpt
- The similarity scores between the query and documents are computed using the cached TF-IDF matrix. ### Applying Caching to Other Parts You can apply similar caching techniques to other parts of your retrieval pipeline: - **Query Par…
See also
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