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@@ -34,7 +34,7 @@ task_ids:
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  # Dataset Card for ssj500k
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- **Important**: there exists another HF implementation of the dataset ([classla/ssj500k](https://huggingface.co/datasets/classla/ssj500k)), but **this one is designed for more general use**. The CLASSLA version seems to expose only the specific training/validation/test annotations used in the CLASSLA library itself, for only a subset of the data.
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  ### Dataset Summary
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@@ -106,10 +106,10 @@ The following attributes are present in the most general config (`all_data`). Pl
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  - `lemmas`: a list of strings containing the lemmas in the current sentence;
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  - `msds`: a list of strings containing the morphosyntactic description of words in the current sentence;
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  - `has_ne_ann`: a bool indicating whether the current example has named entities annotated;
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- - `has_ud_dep_ann`: a bool indicating whether the current example has dependencies (in UD style) annotated**;
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- - `has_jos_dep_ann`: a bool indicating whether the current example has dependencies (in JOS style) annotated**;
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- - `has_srl_ann`: a bool indicating whether the current example has semantic roles annotated**;
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- - `has_mwe_ann`: a bool indicating whether the current example has multi-word expressions annotated**;
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  - `ne_tags`: a list of strings containing the named entity tags encoded using IOB2 - if `has_ne_ann=False` all tokens are annotated with `"N/A"`;
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  - `ud_dep_head`: a list of int32 containing the head index for each word (using UD guidelines) - the head index of the root word is `-1`; if `has_ud_dep_ann=False` all tokens are annotated with `-2`;
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  - `ud_dep_rel`: a list of strings containing the relation with the head for each word (using UD guidelines) - if `has_ud_dep_ann=False` all tokens are annotated with `"N/A"`;
 
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  # Dataset Card for ssj500k
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+ **Important**: there exists another HF implementation of the dataset ([classla/ssj500k](https://huggingface.co/datasets/classla/ssj500k)), but it seems to be more narrowly focused. **This implementation is designed for more general use** - the CLASSLA version seems to expose only the specific training/validation/test annotations used in the CLASSLA library, for only a subset of the data.
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  ### Dataset Summary
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  - `lemmas`: a list of strings containing the lemmas in the current sentence;
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  - `msds`: a list of strings containing the morphosyntactic description of words in the current sentence;
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  - `has_ne_ann`: a bool indicating whether the current example has named entities annotated;
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+ - `has_ud_dep_ann`: a bool indicating whether the current example has dependencies (in UD style) annotated;
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+ - `has_jos_dep_ann`: a bool indicating whether the current example has dependencies (in JOS style) annotated;
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+ - `has_srl_ann`: a bool indicating whether the current example has semantic roles annotated;
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+ - `has_mwe_ann`: a bool indicating whether the current example has multi-word expressions annotated;
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  - `ne_tags`: a list of strings containing the named entity tags encoded using IOB2 - if `has_ne_ann=False` all tokens are annotated with `"N/A"`;
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  - `ud_dep_head`: a list of int32 containing the head index for each word (using UD guidelines) - the head index of the root word is `-1`; if `has_ud_dep_ann=False` all tokens are annotated with `-2`;
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  - `ud_dep_rel`: a list of strings containing the relation with the head for each word (using UD guidelines) - if `has_ud_dep_ann=False` all tokens are annotated with `"N/A"`;