File size: 7,045 Bytes
fcf3ca7
 
 
 
 
2cdc6bc
fcf3ca7
2cdc6bc
fcf3ca7
 
 
 
 
 
 
 
41a4742
fcf3ca7
 
6e260c9
6713094
76a3c88
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fcf3ca7
 
6713094
fcf3ca7
 
 
 
6e260c9
fcf3ca7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c04e150
fcf3ca7
 
 
 
 
 
 
 
 
 
 
 
 
6713094
fcf3ca7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c04e150
 
 
76a3c88
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
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- unknown
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: null
pretty_name: HAREM
dataset_info:
- config_name: default
  features:
  - name: id
    dtype: string
  - name: tokens
    sequence: string
  - name: ner_tags
    sequence:
      class_label:
        names:
          0: O
          1: B-PESSOA
          2: I-PESSOA
          3: B-ORGANIZACAO
          4: I-ORGANIZACAO
          5: B-LOCAL
          6: I-LOCAL
          7: B-TEMPO
          8: I-TEMPO
          9: B-VALOR
          10: I-VALOR
          11: B-ABSTRACCAO
          12: I-ABSTRACCAO
          13: B-ACONTECIMENTO
          14: I-ACONTECIMENTO
          15: B-COISA
          16: I-COISA
          17: B-OBRA
          18: I-OBRA
          19: B-OUTRO
          20: I-OUTRO
  splits:
  - name: test
    num_bytes: 1062714
    num_examples: 128
  - name: train
    num_bytes: 1506373
    num_examples: 121
  - name: validation
    num_bytes: 51318
    num_examples: 8
  download_size: 1887281
  dataset_size: 2620405
- config_name: selective
  features:
  - name: id
    dtype: string
  - name: tokens
    sequence: string
  - name: ner_tags
    sequence:
      class_label:
        names:
          0: O
          1: B-PESSOA
          2: I-PESSOA
          3: B-ORGANIZACAO
          4: I-ORGANIZACAO
          5: B-LOCAL
          6: I-LOCAL
          7: B-TEMPO
          8: I-TEMPO
          9: B-VALOR
          10: I-VALOR
  splits:
  - name: test
    num_bytes: 1062714
    num_examples: 128
  - name: train
    num_bytes: 1506373
    num_examples: 121
  - name: validation
    num_bytes: 51318
    num_examples: 8
  download_size: 1715873
  dataset_size: 2620405
---

# Dataset Card for HAREM

## 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:** [HAREM homepage](https://www.linguateca.pt/primeiroHAREM/harem_coleccaodourada_en.html)
- **Repository:** [HAREM repository](https://www.linguateca.pt/primeiroHAREM/harem_coleccaodourada_en.html)
- **Paper:** [HAREM: An Advanced NER Evaluation Contest for Portuguese](http://comum.rcaap.pt/bitstream/10400.26/76/1/SantosSecoCardosoVilelaLREC2006.pdf)
- **Point of Contact:** [Diana Santos](mailto:[email protected])

### Dataset Summary

The HAREM is a Portuguese language corpus commonly used for Named Entity Recognition tasks. It includes about 93k words, from 129 different texts,
from several genres, and language varieties. The split of this dataset version follows the division made by [1], where 7% HAREM
documents are the validation set and the miniHAREM corpus (with about 65k words) is the test set. There are two versions of the dataset set,
a version that has a total of 10 different named entity classes (Person, Organization, Location, Value, Date, Title, Thing, Event,
Abstraction, and Other) and a "selective" version with only 5 classes (Person, Organization, Location, Value, and Date).

It's important to note that the original version of the HAREM dataset has 2 levels of NER details, namely "Category" and "Sub-type".
The dataset version processed here ONLY USE the "Category" level of the original dataset.

[1] Souza, Fábio, Rodrigo Nogueira, and Roberto Lotufo. "BERTimbau: Pretrained BERT Models for Brazilian Portuguese." Brazilian Conference on Intelligent Systems. Springer, Cham, 2020.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

Portuguese

## Dataset Structure

### Data Instances

```
{
  "id": "HAREM-871-07800",
  "ner_tags": [3, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4,
  ],
  "tokens": [
    "Abraço", "Página", "Principal", "ASSOCIAÇÃO", "DE", "APOIO", "A", "PESSOAS", "COM", "VIH", "/", "SIDA"
  ]
}
```

### Data Fields

- `id`: id of the sample
- `tokens`: the tokens of the example text
- `ner_tags`: the NER tags of each token

The NER tags correspond to this list:
```
"O", "B-PESSOA", "I-PESSOA", "B-ORGANIZACAO", "I-ORGANIZACAO", "B-LOCAL", "I-LOCAL", "B-TEMPO", "I-TEMPO", "B-VALOR", "I-VALOR", "B-ABSTRACCAO", "I-ABSTRACCAO", "B-ACONTECIMENTO", "I-ACONTECIMENTO", "B-COISA", "I-COISA", "B-OBRA", "I-OBRA", "B-OUTRO", "I-OUTRO"
```

The NER tags have the same format as in the CoNLL shared task: a B denotes the first item of a phrase and an I any non-initial word.

### Data Splits

The data is split into train, validation and test set for each of the two versions (default and selective). The split sizes are as follow:

| Train  | Val   | Test |
| ------ | ----- | ---- |
| 121    | 8     | 128  |

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

```
@inproceedings{santos2006harem,
  title={Harem: An advanced ner evaluation contest for portuguese},
  author={Santos, Diana and Seco, Nuno and Cardoso, Nuno and Vilela, Rui},
  booktitle={quot; In Nicoletta Calzolari; Khalid Choukri; Aldo Gangemi; Bente Maegaard; Joseph Mariani; Jan Odjik; Daniel Tapias (ed) Proceedings of the 5 th International Conference on Language Resources and Evaluation (LREC'2006)(Genoa Italy 22-28 May 2006)},
  year={2006}
}
```

### Contributions

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