Dataset class for query-passage pairs
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Dataset class for query-passage pairs has 21 facts recorded in Dontopedia across 4 references, with 2 live disagreements.
Mostly:has method(5), rdf:type(3), class name(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.
createdByCreated by(1)
- Dataset Instance
ex:dataset-instance
definesClassDefines Class(1)
- Python Code 3
ex:python-code-3
hasTypeHas Type(1)
- Query Dataset
ex:QueryDataset
rdf:typeRdf:type(1)
- Query Dataset
ex:QueryDataset
Other facts (20)
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 Method | Init | [2] |
| Has Method | Len | [2] |
| Has Method | Getitem | [2] |
| Has Method | Init Method | [3] |
| Has Method | Getitem Method | [3] |
| Rdf:type | Class | [1] |
| Rdf:type | Python Class | [2] |
| Rdf:type | Py Torch Dataset | [3] |
| Class Name | Dataset | [1] |
| Method | from_list | [1] |
| Has Static Method | from_list | [1] |
| Library | datasets | [1] |
| Is Instance | Torch Dataset | [3] |
| Implements Protocol | Python Dataset Protocol | [3] |
| Designed for | Sentence Transformation Task | [3] |
| Enables | Data Loading | [3] |
| Follows Py Torch Convention | Torch.utils.data.dataset | [3] |
| Is Custom Implementation | Torch.utils.data.dataset | [3] |
| Is Designed for | Sentence Embedding Task | [3] |
| Inherits From | torch.utils.data.Dataset | [4] |
Timeline
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References (4)
ctx:claims/beam/dd70947c-4248-476f-8469-578a9c29f3c1- full textbeam-chunktext/plain1 KB
doc:beam/dd70947c-4248-476f-8469-578a9c29f3c1Show excerpt
Use specialized models trained specifically for the rare language. 6. **Hybrid Approach**: Combine the strengths of multilingual models with language-specific models. 7. **Fallback Mechanisms**: Implement fallback mechanisms to h…
ctx:claims/beam/465dcb64-9710-4e90-8651-452b28528272- full textbeam-chunktext/plain1 KB
doc:beam/465dcb64-9710-4e90-8651-452b28528272Show excerpt
def __init__(self, texts, tokenizer): self.texts = texts self.tokenizer = tokenizer def __len__(self): return len(self.texts) def __getitem__(self, idx): inputs = self.tokenizer(self.tex…
ctx:claims/beam/ed1fe5c9-0d2f-425a-9888-9c4101e2d59a- full textbeam-chunktext/plain1 KB
doc:beam/ed1fe5c9-0d2f-425a-9888-9c4101e2d59aShow excerpt
def __init__(self, queries, passages, tokenizer): self.queries = queries self.passages = passages self.tokenizer = tokenizer def __getitem__(self, idx): query = self.queries[idx] passage = se…
ctx:claims/beam/fa1ef1c1-24c6-4f98-8255-600e4bf6a46c- full textbeam-chunktext/plain1 KB
doc:beam/fa1ef1c1-24c6-4f98-8255-600e4bf6a46cShow excerpt
max_length=context_window, padding='max_length', truncation=True, return_attention_mask=True, return_tensors='pt' ) return { 'query': query, …
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