File size: 5,357 Bytes
dfdb89a
 
 
 
 
 
 
df3de3b
dfdb89a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
54ae770
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82df040
54ae770
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
36047c9
54ae770
 
 
 
 
 
 
 
 
 
36047c9
 
 
54ae770
 
 
36047c9
54ae770
36047c9
 
093ff9f
36047c9
 
54ae770
6b20bb4
54ae770
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f9ccbc7
54ae770
 
 
 
 
 
 
 
 
 
 
 
 
 
 
31225e1
54ae770
 
 
 
093ff9f
54ae770
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
---
YAML tags:
annotations_creators:
- expert-generated
language_creators:
- found
languages:
- hu
licenses:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: HuCOLA
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conditional-text-generation
task_ids:
- machine-translation
- summarization
- text-simplification
---
# Dataset Card for HuCOLA

## Table of Contents
- [Table of Contents](#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:**
[HuCOLA dataset](https://github.com/nytud/HuCOLA)
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
[lnnoemi](mailto:ligeti-nagy.noemi@nytud.hu)

### Dataset Summary

This is the dataset card for the Hungarian Corpus of Linguistic Acceptability (HuCOLA), which is also part of the Hungarian Language Understanding Evaluation Benchmark Kit [HuLU](hulu.nlp.nytud.hu).

### Supported Tasks and Leaderboards




### Languages

The BCP-47 code for Hungarian, the only represented language in this dataset, is hu-HU. 

## Dataset Structure

### Data Instances

For each instance, there is aN id, a sentence and a label.

An example:

```
{"Sent_id": "dev_0",
 "Sent": "A földek eláradtak.",
 "Label": "0"}
```

### Data Fields
- Sent_id: unique id of the instances, an integer between 1 and 1000;
- Sent: a Hungarian sentence;
- label: '0' for wrong, '1' for good sentences.

### Data Splits

HuCOLA has 3 splits: *train*, *validation* and *test*. 

| Dataset split | Number of sentences in the split | Proportion of the split
|---------------|----------------------------------| ---------|
| train         | 7276                              | 80%|
| validation    | 900                             |10%|
| test          | 900                              |10%|

The test data is distributed without the labels. To evaluate your model, please [contact us](mailto:ligeti-nagy.noemi@nytud.hu), or check [HuLU's website](hulu.nlp.nytud.hu) for an automatic evaluation (this feature is under construction at the moment). The evaluation metric is Matthew's correlation coefficient. 

## Dataset Creation

### Source Data

#### Initial Data Collection and Normalization

The data was collected by two human annotators from 3 main linguistic books on Hungarian language: 
 
 - Kiefer Ferenc (ed.) (1992), Strukturális magyar nyelvtan 1. Mondattan. Budapest, Akadémiai Kiadó.
 - Alberti, Gábor and Laczkó, Tibor (eds) (2018), Syntax of Hungarian Nouns and Noun Phrases. I., II. Comprehensive grammar resources. Amsterdam University Press, Amsterdam.
 - Katalin É. Kiss and Veronika Hegedűs (eds) (2021), Postpositions and Postpositional Phrases. Amsterdam: Amsterdam University Press.

The process of collecting sentences partly followed the one described in Warstadt et. al (2018). The guideline of our process is available in the repository of [HuCOLA](https://github.com/nytud/HuCOLA). 


### Annotations

#### Annotation process

Each instance was annotated by 4 human annotators for its acceptability (see the annotation guidelines in the repository of [HuCOLA](https://github.com/nytud/HuCOLA)).

#### Who are the annotators?

The annotators were native Hungarian speakers (of various ages, from 20 to 67) without any linguistic backround.

## Additional Information

### Licensing Information

HuCOLA is released under the CC-BY-SA 4.0 licence.

### Citation Information

If you use this resource or any part of its documentation, please refer to:

Ligeti-Nagy, N., Ferenczi, G., Héja, E., Jelencsik-Mátyus, K., Laki, L. J., Vadász, N., Yang, Z. Gy. and Váradi, T. (2022) HuLU: magyar nyelvű benchmark adatbázis
kiépítése a neurális nyelvmodellek kiértékelése céljából [HuLU: Hungarian benchmark dataset to evaluate neural language models]. XVIII. Magyar Számítógépes Nyelvészeti Konferencia. (in press)
```
@inproceedings{ligetinagy2022hulu,
  title={HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából},
  author={Ligeti-Nagy, N. and Ferenczi, G. and Héja, E. and Jelencsik-Mátyus, K. and Laki, L. J. and Vadász, N. and Yang, Z. Gy. and Váradi, T.},
  booktitle={XVIII. Magyar Számítógépes Nyelvészeti Konferencia},
  year={2022}
}
```


### Contributions

Thanks to [lnnoemi](https://github.com/lnnoemi) for adding this dataset.