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README.md

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----
-annotations_creators:
-- expert-generated
-language_creators:
-- found
-language:
-- sl
-license:
-- cc-by-nc-sa-4.0
-multilinguality:
-- monolingual
-size_categories:
-- 10K<n<100K
-- 100K<n<1M
-source_datasets: []
-task_categories:
-- text-classification
-- token-classification
-task_ids: []
-pretty_name: Dataset of Slovene idiomatic expressions SloIE
-tags:
-- idiom-detection
-- multiword-expression-detection
----
-
-# Dataset Card for SloIE
-
-### Dataset Summary
-
-SloIE is a manually labelled dataset of Slovene idiomatic expressions. It contains 29399 sentences with 75 different expressions that can occur with either a literal or an idiomatic meaning, with appropriate manual annotations for each token. The idiomatic expressions were selected from the [Slovene Lexical Database]( (http://hdl.handle.net/11356/1030). Only expressions that can occur with both a literal and an idiomatic meaning were selected. The sentences were extracted from the Gigafida corpus.
-
-For a more detailed description of the dataset, please see the paper Škvorc et al. (2022) - see below.
-
-### Supported Tasks and Leaderboards
-
-Idiom detection.
-
-### Languages
-
-Slovenian.
-
-## Dataset Structure
-
-### Data Instances
-
-A sample instance from the dataset:
-```json
-{
-  'sentence': 'Fantje regljajo v enem kotu, deklice pa svoje obrazke barvajo s pisanimi barvami.', 
-  'expression': 'barvati kaj s črnimi barvami', 
-  'word_order': [11, 10, 12, 13, 14], 
-  'sentence_words': ['Fantje', 'regljajo', 'v', 'enem', 'kotu,', 'deklice', 'pa', 'svoje', 'obrazke', 'barvajo', 's', 'pisanimi', 'barvami.'],
-  'is_idiom': ['*', '*', '*', '*', '*', '*', '*', '*', 'NE', 'NE', 'NE', 'NE', 'NE']
-}
-```
-
-In this `sentence`, the words of the expression "barvati kaj s črnimi barvami" are used in a literal sense, as indicated by the "NE" annotations inside `is_idiom`. The "*" annotations indicate the words are not part of the expression.  
-
-### Data Fields
-
-- `sentence`: raw sentence in string form - **WARNING**: this is at times slightly different from the words inside `sentence_words` (e.g., "..." here could be "." in `sentence_words`);  
-- `expression`: the annotated idiomatic expression;  
-- `word_order`: numbers indicating the positions of tokens that belong to the expression;  
-- `sentence_words`: words in the sentence;  
-- `is_idiom`: a string denoting whether each word has an idiomatic (`"DA"`), literal (`"NE"`), or ambiguous (`"NEJASEN ZGLED"`) meaning. `"*"` means that the word is not part of the expression.  
-
-## Additional Information
-
-### Dataset Curators
-
-Tadej Škvorc, Polona Gantar, Marko Robnik-Šikonja. 
-
-### Licensing Information
-
-CC BY-NC-SA 4.0.
-
-### Citation Information
-
-```
-@article{skvorc2022mice,
-  title = {MICE: Mining Idioms with Contextual Embeddings},
-  journal = {Knowledge-Based Systems},
-  volume = {235},
-  pages = {107606},
-  year = {2022},
-  doi = {https://doi.org/10.1016/j.knosys.2021.107606},
-  url = {https://www.sciencedirect.com/science/article/pii/S0950705121008686},
-  author = {{\v S}kvorc, Tadej and Gantar, Polona and Robnik-{\v S}ikonja, Marko},
-}
-```
-
-### Contributions
-
-Thanks to [@matejklemen](https://github.com/matejklemen) for adding this dataset.

dataset_infos.json

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-{"default": {"description": "SloIE is a manually labelled dataset of Slovene idiomatic expressions. \nIt contains 29,400 sentences with 75 different expressions that can occur with either a literal or an idiomatic meaning, \nwith appropriate manual annotations for each token. The idiomatic expressions were selected from the Slovene Lexical \nDatabase (http://hdl.handle.net/11356/1030). Only expressions that can occur with both a literal and an idiomatic \nmeaning were selected. The sentences were extracted from the Gigafida corpus.\n", "citation": "@article{skvorc2022mice,\ntitle = {MICE: Mining Idioms with Contextual Embeddings},\njournal = {Knowledge-Based Systems},\nvolume = {235},\npages = {107606},\nyear = {2022},\nissn = {0950-7051},\ndoi = {https://doi.org/10.1016/j.knosys.2021.107606},\nurl = {https://www.sciencedirect.com/science/article/pii/S0950705121008686},\nauthor = {{\u000b S}kvorc, Tadej and Gantar, Polona and Robnik-{\u000b S}ikonja, Marko},\n}\n", "homepage": "http://hdl.handle.net/11356/1030", "license": "Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "expression": {"dtype": "string", "id": null, "_type": "Value"}, "word_order": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "sentence_words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "is_idiom": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "sloie", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 15801505, "num_examples": 29399, "dataset_name": "sloie"}}, "download_checksums": {"https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1335/SloIE.zip": {"num_bytes": 4425132, "checksum": "26602f475742c4717c7bfaa32e6d66b98220dfb5c7dc010d1b1cc8e7eb9a33b1"}}, "download_size": 4425132, "post_processing_size": null, "dataset_size": 15801505, "size_in_bytes": 20226637}}

default/sloie-train.parquet

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sloie.py

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-""" SloIE is a manually labelled dataset of Slovene idiomatic expressions. """
-
-
-import os
-
-import datasets
-
-_CITATION = """\
-@article{skvorc2022mice,
-title = {MICE: Mining Idioms with Contextual Embeddings},
-journal = {Knowledge-Based Systems},
-volume = {235},
-pages = {107606},
-year = {2022},
-issn = {0950-7051},
-doi = {https://doi.org/10.1016/j.knosys.2021.107606},
-url = {https://www.sciencedirect.com/science/article/pii/S0950705121008686},
-author = {{\v S}kvorc, Tadej and Gantar, Polona and Robnik-{\v S}ikonja, Marko},
-}
-"""
-
-_DESCRIPTION = """\
-SloIE is a manually labelled dataset of Slovene idiomatic expressions. 
-It contains 29,400 sentences with 75 different expressions that can occur with either a literal or an idiomatic meaning, 
-with appropriate manual annotations for each token. The idiomatic expressions were selected from the Slovene Lexical 
-Database (http://hdl.handle.net/11356/1030). Only expressions that can occur with both a literal and an idiomatic 
-meaning were selected. The sentences were extracted from the Gigafida corpus.
-"""
-
-_HOMEPAGE = "http://hdl.handle.net/11356/1030"
-
-_LICENSE = "Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)"
-
-_URLS = {
-    "sloie": "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1335/SloIE.zip"
-}
-
-
-class SloIE(datasets.GeneratorBasedBuilder):
-    """ SloIE is a manually labelled dataset of Slovene idiomatic expressions. """
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "sentence": datasets.Value("string"),
-                "expression": datasets.Value("string"),
-                "word_order": datasets.Sequence(datasets.Value("int32")),
-                "sentence_words": datasets.Sequence(datasets.Value("string")),
-                "is_idiom": datasets.Sequence(datasets.Value("string"))
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        urls = _URLS["sloie"]
-        data_dir = dl_manager.download_and_extract(urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"file_path": os.path.join(data_dir, "SloIE.txt")}
-            )
-        ]
-
-    def _generate_examples(self, file_path):
-        idx_instance = 0
-        with open(file_path, "r", encoding="utf-8") as f:
-            line = f.readline().strip()
-            while line:
-                assert line.startswith("#")
-                sent = line[1:]  # Remove initial "#"
-                word_order = list(map(int, f.readline().strip().split(" ")))
-                expression = ""
-                sentence_words, idiomaticity = [], []
-
-                line = f.readline().strip()
-                while line:
-                    token_info = line.split("\t")
-                    word, is_idiomatic_str, expression = token_info
-                    sentence_words.append(word)
-                    idiomaticity.append(is_idiomatic_str)
-
-                    line = f.readline().strip()
-                    # Encountered start of the next sentence - Note that "#" may also be an annotated word, hence the second condition
-                    if line.startswith("#") and len(line.split("\t")) == 1:
-                        break
-
-                yield idx_instance, {
-                    "sentence": sent,
-                    "expression": expression,
-                    "word_order": word_order,
-                    "sentence_words": sentence_words,
-                    "is_idiom": idiomaticity
-                }
-                idx_instance += 1