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Dense Retrieval Dataset

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)

Dense Retrieval Dataset has 19 facts recorded in Dontopedia across 3 references, with 4 live disagreements.

19 facts·10 predicates·3 sources·4 in dispute

Mostly:has attribute(6), requires(3), rdf:type(2)

Maturity scale raw canonical shape-checked rule-derived certified

Has Attributein disputehasAttribute

  • Passages[1]sourceall time · F3e21318 9145 4c42 B0ba 4224ef6163ba
  • Queries[1]sourceall time · F3e21318 9145 4c42 B0ba 4224ef6163ba
  • Tokenizer[1]sourceall time · F3e21318 9145 4c42 B0ba 4224ef6163ba
  • return_attention_mask[2]sourceall time · 503d566f 4b98 4b5e A567 8579fbcf1e30
  • return_tensors[2]sourceall time · 503d566f 4b98 4b5e A567 8579fbcf1e30
  • truncation[2]sourceall time · 503d566f 4b98 4b5e A567 8579fbcf1e30

Rdf:typein disputerdf:type

Requiresin disputerequires

  • Passages[2]sourceall time · 503d566f 4b98 4b5e A567 8579fbcf1e30
  • Queries[2]sourceall time · 503d566f 4b98 4b5e A567 8579fbcf1e30
  • Tokenizer[2]sourceall time · 503d566f 4b98 4b5e A567 8579fbcf1e30

Inherits Fromin disputeinheritsFrom

Implementsimplements

  • Getitem[2]all time · 503d566f 4b98 4b5e A567 8579fbcf1e30

Is Subclass ofisSubclassOf

Len Returns__len__Returns

  • len(self.queries)[2]sourceall time · 503d566f 4b98 4b5e A567 8579fbcf1e30

Has MethodhasMethod

  • __len__[2]sourceall time · 503d566f 4b98 4b5e A567 8579fbcf1e30

Returnsreturns

Rdfs:labelrdfs:label

  • DenseRetrievalDataset[3]all time · 864c2d75 2f47 4635 8d2e 4fe6efdd0312

Inbound mentions (2)

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.

initializedWithInitialized With(1)

iteratesOverIterates Over(1)

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.

19 undated
—
hasAttributebeam/f3e21318-9145-4c42-b0ba-4224ef6163ba
ex:passages
—
hasAttributebeam/f3e21318-9145-4c42-b0ba-4224ef6163ba
ex:queries
—
hasAttributebeam/f3e21318-9145-4c42-b0ba-4224ef6163ba
ex:tokenizer
—
hasAttributebeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
return_attention_mask
—
hasAttributebeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
return_tensors
—
hasAttributebeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
truncation
—
hasMethodbeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
__len__
—
implementsbeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
ex:__getitem__
—
inheritsFrombeam/864c2d75-2f47-4635-8d2e-4fe6efdd0312
ex:Dataset
—
inheritsFrombeam/864c2d75-2f47-4635-8d2e-4fe6efdd0312
ex:Dataset-class
—
isSubclassOfbeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
ex:torch.utils.data.Dataset
—
__len__Returnsbeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
len(self.queries)
—
labelbeam/864c2d75-2f47-4635-8d2e-4fe6efdd0312
DenseRetrievalDataset
—
typebeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
ex:Class
—
typebeam/864c2d75-2f47-4635-8d2e-4fe6efdd0312
ex:PyTorchDataset
—
requiresbeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
ex:passages
—
requiresbeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
ex:queries
—
requiresbeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
ex:tokenizer
—
returnsbeam/503d566f-4b98-4b5e-a567-8579fbcf1e30
ex:dictionary

References (3)

3 references
  1. [1]beam-chunk3 facts
    customctx:claims/beam/f3e21318-9145-4c42-b0ba-4224ef6163ba
    • full textbeam-chunk
      text/plain1 KBdoc:beam/f3e21318-9145-4c42-b0ba-4224ef6163ba
      Show excerpt
      ### 6. **Batch Normalization** Batch normalization normalizes the inputs of each layer, which can help stabilize and speed up training while also acting as a form of regularization. ### Implementation Example Here's how you can incorporat…
  2. [2]beam-chunk12 facts
    customctx:claims/beam/503d566f-4b98-4b5e-a567-8579fbcf1e30
    • full textbeam-chunk
      text/plain1 KBdoc:beam/503d566f-4b98-4b5e-a567-8579fbcf1e30
      Show excerpt
      truncation=True, return_attention_mask=True, return_tensors='pt' ) return { 'query': query_encoding, 'passage': passage_encoding } def __len__(self): …
  3. [3]beam-chunk4 facts
    customctx:claims/beam/864c2d75-2f47-4635-8d2e-4fe6efdd0312
    • full textbeam-chunk
      text/plain1 KBdoc:beam/864c2d75-2f47-4635-8d2e-4fe6efdd0312
      Show excerpt
      - **Margin**: Adjust the margin in contrastive loss functions to penalize incorrect predictions more heavily. ### 5. **Evaluation Metrics** - **Precision@k**: Monitor Precision@k metrics during training to ensure the model is improvi…

See also

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