Create README.md

README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+language:
+- pl
+license:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: NLPre-PL_dataset
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+tags:
+- National Corpus of Polish
+- Narodowy Korpus Języka Polskiego
+task_categories:
+- token-classification
+task_ids:
+- part-of-speech
+- lemmatization
+- parsing
+dataset_info:
+- config_name: nlprepl_by_name
+  features:
+  - name: idx
+    dtype: string
+  - name: text
+    dtype: string
+  - name: tokens
+    sequence: string
+  - name: lemmas
+    sequence: string
+  - name: upos
+    sequence:
+      class_label:
+        names:
+          '0': NOUN
+          '1': PUNCT
+          '2': ADP
+          '3': NUM
+          '4': SYM
+          '5': SCONJ
+          '6': ADJ
+          '7': PART
+          '8': DET
+          '9': CCONJ
+          '10': PROPN
+          '11': PRON
+          '12': X
+          '13': _
+          '14': ADV
+          '15': INTJ
+          '16': VERB
+          '17': AUX
+  - name: xpos
+    sequence: string
+  - name: feats
+    sequence: string
+  - name: head
+    sequence: string
+  - name: deprel
+    sequence: string
+  - name: deps
+    sequence: string
+  - name: misc
+    sequence: string
+  splits:
+  - name: train
+    num_bytes: 3523113
+    num_examples: 1315
+  - name: validation
+    num_bytes: 547285
+    num_examples: 194
+  - name: test
+    num_bytes: 1050299
+    num_examples: 425
+  download_size: 3088237
+  dataset_size: 5120697
+- config_name: nlprepl_by_type
+  features:
+  - name: idx
+    dtype: string
+  - name: text
+    dtype: string
+  - name: tokens
+    sequence: string
+  - name: lemmas
+    sequence: string
+  - name: upos
+    sequence:
+      class_label:
+        names:
+          '0': NOUN
+          '1': PUNCT
+          '2': ADP
+          '3': NUM
+          '4': SYM
+          '5': SCONJ
+          '6': ADJ
+          '7': PART
+          '8': DET
+          '9': CCONJ
+          '10': PROPN
+          '11': PRON
+          '12': X
+          '13': _
+          '14': ADV
+          '15': INTJ
+          '16': VERB
+          '17': AUX
+  - name: xpos
+    sequence: string
+  - name: feats
+    sequence: string
+  - name: head
+    sequence: string
+  - name: deprel
+    sequence: string
+  - name: deps
+    sequence: string
+  - name: misc
+    sequence: string
+  splits:
+  - name: train
+    num_bytes: 3523113
+    num_examples: 1315
+  - name: validation
+    num_bytes: 547285
+    num_examples: 194
+  - name: test
+    num_bytes: 1050299
+    num_examples: 425
+  download_size: 3088237
+  dataset_size: 5120697
+---
+# Dataset Card for NLPre-PL – fairly divided version of NKJP1M
+
+### Dataset Summary
+
+This is the official NLPre-PL dataset - a uniformly paragraph-level divided version of NKJP1M corpus – the 1-million token balanced subcorpus of the National Corpus of Polish (Narodowy Korpus Języka Polskiego)
+
+The NLPre dataset aims at fairly dividing the paragraphs length-wise and topic-wise into train, development, and test sets. Thus, we ensure a similar number of segments
+distribution per paragraph and avoid the situation when paragraphs with a small (or large) number of segments are available only e.g. during test time.
+
+We treat paragraphs as indivisible units (to ensure there is no data leakage between different dataset types). The paragraphs inherit the corresponding document's ID and type (a book, an article, etc.).
+
+We provide two variations of the dataset, based on the fair division of paragraphs:
+- fair by document's ID
+- fair by document's type
+
+### Creation of the dataset
+
+We investigate the distribution over the number of segments in each paragraph. Being Gaussian-like, we divide the paragraphs into 10 buckets of roughly similar size and then sample from them with respective ratios of 0.8 : 0.1 : 0.1 
+(corresponding to training, development, and testing subsets). 
+This data selection technique assures a similar distribution of segment numbers per paragraph in our three subsets. We call it **fair_by_name** (shortly: **by_name**) 
+since it is divided equitably regarding the unique IDs of the documents.
+
+For creating our second split, we also consider the type of document a paragraph belongs to. We first group paragraphs into categories equal to the document types,
+and then we repeat the above-mentioned procedure per category. This provides us with a second split: **fair_by_type** (shortly: **by_type**).
+
+### Supported Tasks and Leaderboards
+
+This resource can be mainly used for training the morphosyntactic analyzer models for Polish. It support such tasks as: lemmatization, part-of-speech recognition, dependency parsing.
+
+### Languages
+
+Polish (monolingual)
+
+## Dataset Structure
+
+### Data Instances
+
+```
+{'nkjp_text': 'NKJP_1M_1102000002',
+ 'nkjp_par': 'morph_1-p',
+ 'nkjp_sent': 'morph_1.18-s',
+ 'tokens': ['-', 'Nie', 'mam', 'pieniędzy', ',', 'da', 'mi', 'pani', 'wywiad', '?'],
+ 'lemmas': ['-', 'nie', 'mieć', 'pieniądz', ',', 'dać', 'ja', 'pani', 'wywiad', '?'],
+ 'cposes': [8, 11, 10, 9, 8, 10, 9, 9, 9, 8],
+ 'poses': [19, 25, 12, 35, 19, 12, 28, 35, 35, 19],
+ 'tags': [266, 464, 213, 923, 266, 218, 692, 988, 961, 266],
+ 'nps': [False, False, False, False, True, False, False, False, False, True],
+ 'nkjp_ids': ['morph_1.9-seg', 'morph_1.10-seg', 'morph_1.11-seg', 'morph_1.12-seg', 'morph_1.13-seg', 'morph_1.14-seg', 'morph_1.15-seg', 'morph_1.16-seg', 'morph_1.17-seg', 'morph_1.18-seg']}
+```
+
+### Data Fields
+
+- `nkjp_text`, `nkjp_par`, `nkjp_sent` (strings): XML identifiers of the present text (document), paragraph and sentence in NKJP. (These allow to map the data point back to the source corpus and to identify paragraphs/samples.)
+- `tokens` (sequence of strings): tokens of the text defined as in NKJP.
+- `lemmas` (sequence of strings): lemmas corresponding to the tokens.
+- `tags` (sequence of labels): morpho-syntactic tags according to Morfeusz2 tagset (1019 distinct tags).
+- `poses` (sequence of labels): flexemic class (detailed part of speech, 40 classes) – the first element of the corresponding tag.
+- `cposes` (sequence of labels): coarse part of speech (13 classes): all verbal and deverbal flexemic classes get mapped to a `V`, nominal – `N`, adjectival – `A`, “strange” (abbreviations, alien elements, symbols, emojis…)  – `X`, rest as in `poses`.
+- `nps` (sequence of booleans): `True` means that the corresponding token is not preceded by a space in the source text.
+- `nkjp_ids` (sequence of strings): XML identifiers of particular tokens in NKJP (probably an overkill).
+
+### Data Splits
+
+|           | Train  | Validation | Test   |
+| -----     | ------ | -----      | ----   |
+| sentences | 68943  | 7755       |  8964  |
+| tokens    | 978368 | 112454     | 125059 |
+
+
+## Licensing Information
+
+![Creative Commons License](https://i.creativecommons.org/l/by/4.0/80x15.png) This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/).
+
+
+<!--
+### Contributions
+
+Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
+-->