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@@ -21,4 +21,82 @@ configs:
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  data_files:
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  - split: train
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  path: data/train-*
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  data_files:
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  - split: train
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  path: data/train-*
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+ license: cc-by-4.0
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+ language:
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+ - da
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+ pretty_name: Danish Compounds
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+ size_categories:
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+ - n<1K
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  ---
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+
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+ ## Danish Compounds
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+
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+ Danish Compounds consists of a list of Danish compound words as well as an annotation of how they were split. This can be used to evaluate how close a model can obtain similar splits.
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+
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+ ## Loading the dataset
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+
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+ To load the dataset simply run:
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+
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+ ```py
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+ from datasets import load_dataset
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+
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+ ds = load_dataset("KennethEnevoldsen/danish-compounds", split="train")
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+ ```
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+
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+
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+ ## Sample
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+
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+ A sample from the dataset looks as follows:
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+
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+ ```py
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+ {
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+ "words": "A-aktie",
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+ "annotated_splits": "A|-|aktie",
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+ "splits": [["A"], ["-"], ["aktie"]],
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+ "source": "wiktionary",
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+ }
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+ ```
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+
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+ Where:
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+
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+ - `words`: The word as a string
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+ - `annotated_splits`: The annotated splits, including primary and secondary splits
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+ - `splits`: The words.
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+ - `source` Where the word was found.
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+
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+ ## Dataset Source
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+
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+ The dataset is derived from two source [Wiktionary](https://da.wiktionary.org/wiki/Kategori:Sammensatte_ord_på_dansk) and [sproget.dk](https://sproget.dk/raad-og-regler/ordlister/sproglige-ordlister/ordforbindelser-i-et-eller-flere-ord).
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+
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+
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+ ## Annotation Creator
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+
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+ The word splits were manually annotated by Kenneth Enevoldsen.
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+
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+ ## Annotation Scheme
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+ Words that the annotator did not understand (e.g. some Icelandic words) were removed.
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+
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+ - "|" indicates primary split (into compound words)
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+ - "&" indicates secondary split (used in case of compound word existing of a multiple compounds) e.g. blindtarmsbetændelse consist of two compounds "blindtarm" "betændelse" with a 'lim-s' ("s"), but blindtarm is itself a compound, namely "blind", "tarm".
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+
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+ ## Reason for annotation
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+
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+ This dataset was initially annotated to get a gist of how well BPE, Unigram, and similar tokenizers obtain tokens similar to conventional splits.
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5ff5943752c26e9bc240bada/tdTHo4W-_36-1U1gSR8CI.png)
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+
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+ It was annotated as a part of Kenneth Enevoldsen's master thesis.
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+
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+ ## Citation
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+
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+ If you use this work please cite:
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+
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+ ```
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+ @mastersthesis{Enevoldsen2022,
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+ title = {Representation Learning for Decision-Support in Clinical Psychiatry},
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+ author = {Kenneth Enevoldsen},
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+ year = {2022},
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+ school = {Aarhus University},
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+ note = {Master's Thesis}
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+ }
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+ ```