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newmindai
/

regulation-retrieval

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Question Answering

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nmmursit commited on 1 day ago

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@@ -208,7 +208,7 @@ On average, each özelge is represented by around **5.1 distinct queries**, corr
 In other words, roughly **61% of the corpus has 5 or more query types populated**, making them rich multi-perspective legal cases rather than shallow single-label examples.
-![Queries per document distribution](https://huggingface.co/datasets/newmindai/regulation-retrieval/blob/main/ozelge_queries_per_doc.png)
 ### Text Length Distribution
@@ -228,7 +228,7 @@ For **query texts** (legal snippets extracted from seven perspectives across all
 This makes queries similar to short legal questions, issue statements, justifications or excerpts from statutes/communiques, while the associated corpus entries provide the full ruling context for the subset of records where the full original özelge text is available.
-![Corpus vs. query text length histograms](https://huggingface.co/datasets/newmindai/regulation-retrieval/blob/main/ozelge_text_length_hist.png)
 ## Use Cases

 In other words, roughly **61% of the corpus has 5 or more query types populated**, making them rich multi-perspective legal cases rather than shallow single-label examples.
+![Queries per document distribution](https://huggingface.co/datasets/newmindai/regulation-retrieval/resolve/main/ozelge_queries_per_doc.png)
 ### Text Length Distribution
 This makes queries similar to short legal questions, issue statements, justifications or excerpts from statutes/communiques, while the associated corpus entries provide the full ruling context for the subset of records where the full original özelge text is available.
+![Corpus vs. query text length histograms](https://huggingface.co/datasets/newmindai/regulation-retrieval/resolve/main/ozelge_text_length_hist.png)
 ## Use Cases