README.md

---
annotations_creators:
- expert-generated
language:
- pl
language_creators:
- expert-generated
- found
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: wsd-polish-datasets
size_categories:
- 1M<n<10M
source_datasets:
- original
tags: []
task_categories:
- token-classification
task_ids:
- word-sense-disambiguation
---
# Word Sense Disambiguation Corpora for Polish

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:**
- **Repository:**
- **Paper:** https://link.springer.com/chapter/10.1007/978-3-031-08754-7_70
- **Point of Contact:** [email protected]

### Dataset Summary

`WSD Polish Datasets` is a comprehensive benchmark for word sense disambiguation (WSD) classification task in Polish language.
It consists of 7 distinct datasets, manually annotated with senses from plWordNet-4.5 sense inventory. The following datasets
were annotated and included into our benchmark:
- KPWr
- KPWr-100
- Sherlock (SPEC)
- Skladnica
- WikiGlex (a subset of GLEX corpus)
- EmoGlex (a subset of GLEX corpus)
- Walenty


### Supported Tasks and Leaderboards

Word sense disambiguation task. We do not provide a leaderboard. However, we provide an example evaluation script for evaluating WSD models.

### Languages

Polish language, PL

## Dataset Structure

### Data Instances

Data are structured in JSONL format, each single text sample is divided by sentence.

```
{
  "text": "Wpierw pani Hudson została zerwana z łóżka, po czym odegrała się na mnie, a ja - na tobie.",
  "tokens": [
    {
      "index": 0,
      "position": [ 0, 6 ],
      "orth": "Wpierw",
      "lemma": "wpierw",
      "pos": "adv",
      "ctag": "adv"
    },
    {
      "index": 1,
      "position": [ 7, 11 ],
      "orth": "pani",
      "lemma": "pani",
      "pos": "noun",
      "ctag": "subst:nom:f:sg"
    },
    {
      "index": 2,
      "position": [ 12, 18 ],
      "orth": "Hudson",
      "lemma": "Hudson",
      "pos": "noun",
      "ctag": "subst:nom:f:sg"
    },
    {
      "index": 3,
      "position": [ 19, 26 ],
      "orth": "została",
      "lemma": "zostać",
      "pos": "verb",
      "ctag": "praet:perf:f:sg"
    },
    {
      "index": 4,
      "position": [ 27, 34 ],
      "orth": "zerwana",
      "lemma": "zerwać",
      "pos": "verb",
      "ctag": "ppas:perf:nom:f:aff:sg"
    },
   <...>
  ],
  "phrases": [
    {
      "indices": [ 10, 11 ],
      "head": 10,
      "lemma": "odegrać się"
    }
  ],
  "wsd": [
      {
        "index": 0,
        "pl_sense": "wpierw.1.r",
        "plWN_syn_id": "01a4a067-aac5-11ed-aae5-0242ac130002",
        "plWN_lex_id": "f2757c30-aac4-11ed-aae5-0242ac130002",
        "plWN_syn_legacy_id": "477654",
        "plWN_lex_legacy_id": "718454",
        "PWN_syn_id": "00102736-r",
        "bn_syn_id": "bn:00115376r",
        "mapping_relation": "synonymy"
      },
      {
        "index": 1,
        "pl_sense": "pani.2.n",
        "plWN_syn_id": "f35fb1ed-aac4-11ed-aae5-0242ac130002",
        "plWN_lex_id": "d5145565-aac4-11ed-aae5-0242ac130002",
        "plWN_syn_legacy_id": "129",
        "plWN_lex_legacy_id": "20695",
        "PWN_syn_id": "10787470-n",
        "bn_syn_id": "bn:00001530n",
        "mapping_relation": "synonymy"
      },
   <...>
  ]
}
```

### Data Fields

Description of json keys:
- `text`: text of the sentence
- `tokens`: list of tokens made by tokenization process
  - `index`: token order index in sentence
  - `position`: token chars span indices <included, excluded>
  - `orth`: word
  - `lemma`: lemmatised word
  - `pos`: part of speech
  - `ctag`: morphosyntactic tag
- `phrases`: list of multi-word 
- `wsd`: annotation labels for the WSD task

### Data Splits

We do not specify an exact data split for training and evaluation. However, we suggest to use GLEX and Składnica for training and other datasets for testing.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection, Normalization and Post-processing

Source corpora were initially pre-processed using morphosyntactic tagging and multi-word expression recognition tools.
To tokenize and tag the datasets we used [MorphoDiTa](https://clarin-pl.eu/dspace/handle/11321/425) adapted to Polish language. To recognize multi-word expressions
we applied pattern-based matching tool [Corpus2-MWE](https://clarin-pl.eu/dspace/handle/11321/533) - only MWEs from plWordNet were included. After manual annotation, 
sense indices of plWordNet 4.5 were mapped automatically to Princeton WordNet 3.0 and BabelNet 4.0 indices using plWordNet's interlingual mapping.

### Annotations

#### Annotation process

* 2+1 annotation process with inter-annotator agreement score over 0.6 PSA
* annotated with [plWordNet 4.5](http://plwordnet.pwr.wroc.pl/wordnet/)
* software: [WordNet-Loom](https://clarin-pl.eu/dspace/handle/11321/275) and [Inforex](https://clarin-pl.eu/dspace/handle/11321/13)
* both single-word and multi-word expressions annotated
* full-text sense annotation (excluding KPWr)

#### Who are the annotators?

- professional linguists (mention all people involved)

### Personal and Sensitive Information

The datasets do not contain any personal or sensitive information.

## Considerations for Using the Data

### Discussion of Biases

Some datasets are biased towards most frequent senses. (Stats?)

### Other Known Limitations

* sense inventories are usually incomplete therefore some word senses might be missing in plWordNet
* single-word and multi-word terms expressing novel senses (missing in plWordNet) were not marked

## Additional Information

### Dataset Curators

Arkadiusz Janz ([email protected])

### Licensing Information

KPWR-100 [CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)  
KPWR [CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)  
Walenty [CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)  
Sherlock [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/)  
Skladnica [GNU GPL 3](http://www.gnu.org/licenses/gpl-3.0.en.html)  
GLEX [plWordNet License](http://plwordnet.pwr.wroc.pl/wordnet/licence)  


### Citation Information

Main source (all corpora as a unified benchmark)

````
@InProceedings{10.1007/978-3-031-08754-7_70,
  author="Janz, Arkadiusz
  and Dziob, Agnieszka
  and Oleksy, Marcin
  and Baran, Joanna",
  editor="Groen, Derek
  and de Mulatier, Cl{\'e}llia
  and Paszynski, Maciej
  and Krzhizhanovskaya, Valeria V.
  and Dongarra, Jack J.
  and Sloot, Peter M. A.",
  title="A Unified Sense Inventory for Word Sense Disambiguation in Polish",
  booktitle="Computational Science -- ICCS 2022",
  year="2022",
  publisher="Springer International Publishing",
  address="Cham",
  pages="682--689",
  isbn="978-3-031-08754-7"
}

````

Related work
------------

KPWr-100, Składnica, SPEC
````
@article{janzresults,
  title={Results of the PolEval 2020 Shared Task 3: Word Sense Disambiguation},
  author={Janz, Arkadiusz and Chlebus, Joanna and Dziob, Agnieszka and Piasecki, Maciej},
  journal={Proceedings of the PolEval 2020 Workshop},
  pages={65--77},
  year={2020}
}
````

GLEX (EmoGLEX)

````
@article{janz2017plwordnet,
  title={{plWordNet} as a basis for large emotive lexicons of Polish},
  author={Janz, Arkadiusz and Kocon, Jan and Piasecki, Maciej and Zasko-Zielinska, Monika},
  journal={Proceedings of Human Language Technologies as a Challenge for Computer Science and Linguistics Poznan: Fundacja Uniwersytetu im. Adama Mickiewicza w Poznaniu},
  pages={189--193},
  year={2017}
}
````

KPWr
````
@conference{broda2012,
	address = {Istanbul, Turkey},
	author = {Bartosz Broda and Micha{\l} Marci{\'n}czuk and Marek Maziarz and Adam Radziszewski and Adam Wardy{\'n}ski},
	booktitle = {Proceedings of LREC'12},
	owner = {Marlena},
	publisher = {ELRA},
	timestamp = {2014.06.20},
	title = {KPWr: Towards a Free Corpus of Polish},
	year = {2012}
}
````

Składnica
````
@inproceedings{hajnicz-2014-lexico,
    title = "Lexico-Semantic Annotation of Sk{\l}adnica Treebank by means of {PLWN} Lexical Units",
    author = "Hajnicz, El{\.z}bieta",
    booktitle = "Proceedings of the Seventh Global {W}ordnet Conference",
    month = jan,
    year = "2014",
    address = "Tartu, Estonia",
    publisher = "University of Tartu Press",
    url = "https://aclanthology.org/W14-0104",
    pages = "23--31",
}
````

Walenty
````
@inproceedings{haj:and:bar:lrec16,
	author = {Hajnicz, El{\.z}bieta and Andrzejczuk, Anna and Bartosiak, Tomasz},
	crossref = {lrec:16},
	pages = {2625--2632},
	pdf = {http://www.lrec-conf.org/proceedings/lrec2016/pdf/382_Paper.pdf},
	title = {Semantic Layer of the Valence Dictionary of {P}olish \emph{{W}alenty}}
}
````

Mapping plWordNet onto Princeton WordNet
````
@inproceedings{rudnicka-etal-2021-non,
    title = "A (Non)-Perfect Match: Mapping pl{W}ord{N}et onto {P}rinceton{W}ord{N}et",
    author = "Rudnicka, Ewa  and
      Witkowski, Wojciech  and
      Piasecki, Maciej",
    booktitle = "Proceedings of the 11th Global Wordnet Conference",
    month = jan,
    year = "2021",
    address = "University of South Africa (UNISA)",
    publisher = "Global Wordnet Association",
    url = "https://aclanthology.org/2021.gwc-1.16",
    pages = "137--146"
}
````