Dontopedia

Score Combination

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Score Combination has 7 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

7 facts·6 predicates·2 sources·1 in dispute

Mostly:combines(2), rdf:type(1), uses combination method(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (2)

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containsContains(1)

enablesEnables(1)

Other facts (7)

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7 facts
PredicateValueRef
CombinesBm25 Scores[1]
CombinesDense Scores[1]
Rdf:typeProcess[1]
Uses Combination MethodWeighted Sum[1]
Uses ParameterAlpha[1]
UsesWeights[2]
Formulaweights[0] * sparse_scores_normalized + weights[1] * dense_scores_normalized[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.

typebeam/b0390377-17cd-4838-999f-26ca02c6c6a4
ex:Process
combinesbeam/b0390377-17cd-4838-999f-26ca02c6c6a4
ex:bm25-scores
combinesbeam/b0390377-17cd-4838-999f-26ca02c6c6a4
ex:dense-scores
usesCombinationMethodbeam/b0390377-17cd-4838-999f-26ca02c6c6a4
ex:weighted-sum
usesParameterbeam/b0390377-17cd-4838-999f-26ca02c6c6a4
ex:alpha
usesbeam/cbd5706c-a35a-4d21-8563-796e0069e167
ex:weights
formulabeam/cbd5706c-a35a-4d21-8563-796e0069e167
weights[0] * sparse_scores_normalized + weights[1] * dense_scores_normalized

References (2)

2 references
  1. ctx:claims/beam/b0390377-17cd-4838-999f-26ca02c6c6a4
    • full textbeam-chunk
      text/plain963 Bdoc:beam/b0390377-17cd-4838-999f-26ca02c6c6a4
      Show excerpt
      - We use a pre-trained BERT model to generate embeddings for documents and the query. - `cosine_similarity` computes the similarity between the query embedding and document embeddings. 3. **Combining Scores**: - We combine the BM2
  2. ctx:claims/beam/cbd5706c-a35a-4d21-8563-796e0069e167
    • full textbeam-chunk
      text/plain1 KBdoc:beam/cbd5706c-a35a-4d21-8563-796e0069e167
      Show excerpt
      # Validate input dimensions if sparse_scores.shape != dense_scores.shape: raise ValueError("Mismatched dimensions between sparse and dense scores") # Normalize scores to ensure they are on the same scale

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