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  2. NoisyNER_labelset1/noisyner-test.parquet +3 -0
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  24. data/NoisyNER_labelset1_all.tsv +0 -0
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README.md DELETED
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- ---
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- annotations_creators:
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- - expert-generated
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- language:
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- - et
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- language_creators:
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- - found
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- license:
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- - cc-by-nc-4.0
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- multilinguality:
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- - monolingual
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- paperswithcode_id: noisyner
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- pretty_name: NoisyNER
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- size_categories:
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- - 10K<n<100K
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- source_datasets:
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- - original
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- tags:
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- - newspapers
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- - 1997-2009
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- task_categories:
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- - token-classification
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- task_ids:
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- - named-entity-recognition
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- ---
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-
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- # Dataset Card for NoisyNER
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-
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- ## Table of Contents
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- - [Table of Contents](#table-of-contents)
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- - [Dataset Description](#dataset-description)
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- - [Dataset Summary](#dataset-summary)
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- - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- - [Languages](#languages)
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- - [Dataset Structure](#dataset-structure)
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- - [Data Instances](#data-instances)
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- - [Data Fields](#data-fields)
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- - [Data Splits](#data-splits)
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- - [Dataset Creation](#dataset-creation)
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- - [Curation Rationale](#curation-rationale)
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- - [Source Data](#source-data)
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- - [Annotations](#annotations)
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- - [Personal and Sensitive Information](#personal-and-sensitive-information)
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- - [Considerations for Using the Data](#considerations-for-using-the-data)
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- - [Social Impact of Dataset](#social-impact-of-dataset)
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- - [Discussion of Biases](#discussion-of-biases)
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- - [Other Known Limitations](#other-known-limitations)
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- - [Additional Information](#additional-information)
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- - [Dataset Curators](#dataset-curators)
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- - [Licensing Information](#licensing-information)
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- - [Citation Information](#citation-information)
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- - [Contributions](#contributions)
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-
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- ## Dataset Description
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-
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- - **Repository:** [Estonian NER corpus](https://doi.org/10.15155/1-00-0000-0000-0000-00073L), [NoisyNER dataset](https://github.com/uds-lsv/NoisyNER)
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- - **Paper:** [Named Entity Recognition in Estonian](https://aclanthology.org/W13-2412/), [Analysing the Noise Model Error for Realistic Noisy Label Data](https://arxiv.org/abs/2101.09763)
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- - **Dataset:** NoisyNER
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- - **Domain:** News
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-
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- ### Dataset Summary
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-
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- NoisyNER is a dataset for the evaluation of methods to handle noisy labels when training machine learning models.
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-
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- - Entity Types: `PER`, `ORG`, `LOC`
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-
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- It is from the NLP/Information Extraction domain and was created through a realistic distant supervision technique. Some highlights and interesting aspects of the data are:
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-
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- - Seven sets of labels with differing noise patterns to evaluate different noise levels on the same instances
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- - Full parallel clean labels available to compute upper performance bounds or study scenarios where a small amount of gold-standard data can be leveraged
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- - Skewed label distribution (typical for Named Entity Recognition tasks)
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- - For some label sets: noise level higher than the true label probability
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- - Sequential dependencies between the labels
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-
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- For more details on the dataset and its creation process, please refer to the original author's publication https://ojs.aaai.org/index.php/AAAI/article/view/16938 (published at AAAI'21).
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-
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- This dataset is based on the Estonian NER corpus. For more details see https://aclanthology.org/W13-2412/
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-
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- ### Supported Tasks and Leaderboards
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ### Languages
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-
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- The language data in NoisyNER is in Estonian (BCP-47 et)
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-
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- ## Dataset Structure
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-
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- ### Data Instances
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-
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- An example of 'train' looks as follows.
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- ```
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- {
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- 'id': '0',
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- 'tokens': ['Tallinna', 'õhusaaste', 'suureneb', '.'],
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- 'lemmas': ['Tallinn+0', 'õhu_saaste+0', 'suurene+b', '.'],
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- 'grammar': ['_H_ sg g', '_S_ sg n', '_V_ b', '_Z_'],
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- 'ner_tags': [5, 0, 0, 0]
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- }
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- ```
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-
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- ### Data Fields
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-
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- The data fields are the same among all splits.
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-
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- - `id`: a `string` feature.
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- - `tokens`: a `list` of `string` features.
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- - `lemmas`: a `list` of `string` features.
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- - `grammar`: a `list` of `string` features.
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- - `ner_tags`: a `list` of classification labels (`int`). Full tagset with indices:
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-
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- ```python
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- {'O': 0, 'B-PER': 1, 'I-PER': 2, 'B-ORG': 3, 'I-ORG': 4, 'B-LOC': 5, 'I-LOC': 6}
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- ```
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-
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- ### Data Splits
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-
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- The splits are the same across all configurations.
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-
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- |train|validation|test|
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- |----:|---------:|---:|
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- |11365| 1480|1433|
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-
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- ## Dataset Creation
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-
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- ### Curation Rationale
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ### Source Data
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-
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- #### Initial Data Collection and Normalization
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-
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- Tkachenko et al (2013) collected 572 news stories published in the local online newspapers [Delfi](http://delfi.ee/) and [Postimees](http://postimees.ee/) between 1997 and 2009. Selected articles cover both local and international news on a range of topics including politics, economics and sports. The raw text was preprocessed using the morphological disambiguator t3mesta ([Kaalep and
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- Vaino, 1998](https://www.cl.ut.ee/yllitised/kk_yhest_1998.pdf)) provided by [Filosoft](http://www.filosoft.ee/). The processing steps involve tokenization, lemmatization, part-of-speech tagging, grammatical and morphological analysis.
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-
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- #### Who are the source language producers?
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ### Annotations
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-
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- #### Annotation process
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-
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- According to Tkachenko et al (2013) one of the authors manually tagged the corpus and the other author examined the tags, after which conflicting cases were resolved.
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- The total size of the corpus is 184,638 tokens. Tkachenko et al (2013) provide the following number of named entities in the corpus:
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-
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- | | PER | LOC | ORG | Total |
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- |--------|------|------|------|-------|
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- | All | 5762 | 5711 | 3938 | 15411 |
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- | Unique | 3588 | 1589 | 1987 | 7164 |
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-
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- Hedderich et al (2021) obtained the noisy labels through a distant supervision/automatic annotation approach. They extracted lists of named entities from Wikidata and matched them against words in the text via the ANEA tool ([Hedderich, Lange, and Klakow 2021](https://arxiv.org/abs/2102.13129)). They also used heuristic functions to correct errors caused by non-complete lists of entities,
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- grammatical complexities of Estonian that do not allow simple string matching or entity lists in conflict with each other. For instance, they normalized the grammatical form of a word or excluded certain high false-positive words. They provide seven sets of labels that differ in the noise process. This results in 8 different configurations, when added to the original split with clean labels.
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-
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- #### Who are the annotators?
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ### Personal and Sensitive Information
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ## Considerations for Using the Data
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-
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- ### Social Impact of Dataset
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ### Discussion of Biases
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ### Other Known Limitations
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ## Additional Information
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-
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- ### Dataset Curators
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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-
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- ### Licensing Information
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-
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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
187
-
188
-
189
- ### Citation Information
190
-
191
- ```
192
- @inproceedings{tkachenko-etal-2013-named,
193
- title = "Named Entity Recognition in {E}stonian",
194
- author = "Tkachenko, Alexander and
195
- Petmanson, Timo and
196
- Laur, Sven",
197
- booktitle = "Proceedings of the 4th Biennial International Workshop on {B}alto-{S}lavic Natural Language Processing",
198
- month = aug,
199
- year = "2013",
200
- address = "Sofia, Bulgaria",
201
- publisher = "Association for Computational Linguistics",
202
- url = "https://aclanthology.org/W13-2412",
203
- pages = "78--83",
204
- }
205
- @article{Hedderich_Zhu_Klakow_2021,
206
- title={Analysing the Noise Model Error for Realistic Noisy Label Data},
207
- author={Hedderich, Michael A. and Zhu, Dawei and Klakow, Dietrich},
208
- volume={35},
209
- url={https://ojs.aaai.org/index.php/AAAI/article/view/16938},
210
- number={9},
211
- journal={Proceedings of the AAAI Conference on Artificial Intelligence},
212
- year={2021},
213
- month={May},
214
- pages={7675-7684},
215
- }
216
- ```
217
-
218
- ### Contributions
219
-
220
- Thanks to [@phucdev](https://github.com/phucdev) for adding this dataset.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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