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Publish Habr IR retrieval release

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Release fingerprint: 0a18ee0a5ee2373a1b861f1d08d325052ccaeec94fb69110d90d16c2630d96e2

README.md CHANGED
@@ -11,26 +11,16 @@ tags:
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  - russian
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  - synthetic-queries
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  configs:
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- - config_name: pairs
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  data_files:
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  - split: train
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- path: data/pairs/train.parquet
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- - split: validation
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- path: data/pairs/validation.parquet
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  - split: test
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- path: data/pairs/test.parquet
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- - config_name: corpus-100k
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- data_files:
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- - split: train
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- path: data/corpus-100k/corpus.parquet
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- - config_name: qrels
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- data_files:
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- - split: train
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- path: data/qrels/train.parquet
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- - split: validation
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- path: data/qrels/validation.parquet
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- - split: test
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- path: data/qrels/test.parquet
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  ---
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  # Habr IR
@@ -43,18 +33,19 @@ Queries and short answers were generated from passages and passed deterministic
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  and competitor checks. The generation process is synthetic: these examples are not a substitute for fully
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  human-authored relevance judgments. The local pilot was manually reviewed before scale generation.
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- ## Configurations
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- - `pairs`: queries, answers, positive passages, intent labels, and generation provenance.
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- - `corpus-100k`: the complete retrieval corpus; `is_positive` marks passages referenced by accepted pairs.
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- - `qrels`: one positive relevance judgment per query.
 
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  ```python
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  from datasets import load_dataset
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- pairs = load_dataset("justatom/habr-ir", "pairs")
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- corpus = load_dataset("justatom/habr-ir", "corpus-100k", split="train")
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- qrels = load_dataset("justatom/habr-ir", "qrels")
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  ```
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  ## Source and limitations
 
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  - russian
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  - synthetic-queries
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  configs:
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+ - config_name: default
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  data_files:
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  - split: train
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+ path: data/train-*.parquet
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+ - split: dev
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+ path: data/dev-*.parquet
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  - split: test
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+ path: data/test-*.parquet
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+ - split: corpus
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+ path: data/corpus-*.parquet
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Habr IR
 
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  and competitor checks. The generation process is synthetic: these examples are not a substitute for fully
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  human-authored relevance judgments. The local pilot was manually reviewed before scale generation.
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+ ## Splits
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+ - `train`, `dev`, and `test` contain query-positive rows.
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+ - `corpus` contains candidate documents as `doc_id, content`.
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+ - All splits share one schema and one `default` Dataset Viewer configuration.
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+ - Raw qrels, the audit sheet, and release provenance remain downloadable repository artifacts.
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  ```python
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  from datasets import load_dataset
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+ dataset = load_dataset("justatom/habr-ir")
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+ print(dataset["train"][0]["query"])
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+ print(dataset["corpus"][0]["content"])
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  ```
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  ## Source and limitations
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