File size: 8,635 Bytes
0088ca3
9dcf65e
219c181
0c9edd9
18a669e
c639df6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0088ca3
 
 
 
 
 
 
0c9edd9
0088ca3
 
 
 
0c9edd9
0088ca3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7bbd4e9
0088ca3
 
 
 
 
 
 
 
 
7bbd4e9
0088ca3
 
 
 
 
 
 
 
 
 
 
 
0c9edd9
0088ca3
 
 
7bbd4e9
0088ca3
 
 
7bbd4e9
0088ca3
7bbd4e9
0088ca3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7bbd4e9
0088ca3
 
 
 
 
 
 
 
 
0c9edd9
0088ca3
 
 
 
 
7bbd4e9
0088ca3
7bbd4e9
0088ca3
 
 
7bbd4e9
0088ca3
0c9edd9
 
 
 
 
 
0088ca3
 
7bbd4e9
0088ca3
0c9edd9
 
 
 
 
 
0088ca3
 
7bbd4e9
0088ca3
 
 
7bbd4e9
0088ca3
7bbd4e9
0088ca3
 
 
7bbd4e9
0088ca3
 
 
7bbd4e9
0088ca3
 
 
7bbd4e9
0088ca3
7bbd4e9
0088ca3
 
 
7bbd4e9
0088ca3
 
 
7bbd4e9
0088ca3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c639df6
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
259
260
261
262
263
264
265
266
---
language:
- en
paperswithcode_id: conll-2000-1
pretty_name: CoNLL-2000
dataset_info:
  features:
  - name: id
    dtype: string
  - name: tokens
    sequence: string
  - name: pos_tags
    sequence:
      class_label:
        names:
          0: ''''''
          1: '#'
          2: $
          3: (
          4: )
          5: ','
          6: .
          7: ':'
          8: '``'
          9: CC
          10: CD
          11: DT
          12: EX
          13: FW
          14: IN
          15: JJ
          16: JJR
          17: JJS
          18: MD
          19: NN
          20: NNP
          21: NNPS
          22: NNS
          23: PDT
          24: POS
          25: PRP
          26: PRP$
          27: RB
          28: RBR
          29: RBS
          30: RP
          31: SYM
          32: TO
          33: UH
          34: VB
          35: VBD
          36: VBG
          37: VBN
          38: VBP
          39: VBZ
          40: WDT
          41: WP
          42: WP$
          43: WRB
  - name: chunk_tags
    sequence:
      class_label:
        names:
          0: O
          1: B-ADJP
          2: I-ADJP
          3: B-ADVP
          4: I-ADVP
          5: B-CONJP
          6: I-CONJP
          7: B-INTJ
          8: I-INTJ
          9: B-LST
          10: I-LST
          11: B-NP
          12: I-NP
          13: B-PP
          14: I-PP
          15: B-PRT
          16: I-PRT
          17: B-SBAR
          18: I-SBAR
          19: B-UCP
          20: I-UCP
          21: B-VP
          22: I-VP
  splits:
  - name: test
    num_bytes: 1201151
    num_examples: 2013
  - name: train
    num_bytes: 5356965
    num_examples: 8937
  download_size: 3481560
  dataset_size: 6558116
---

# Dataset Card for "conll2000"

## 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:** [https://www.clips.uantwerpen.be/conll2000/chunking/](https://www.clips.uantwerpen.be/conll2000/chunking/)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 3.32 MB
- **Size of the generated dataset:** 6.25 MB
- **Total amount of disk used:** 9.57 MB

### Dataset Summary

 Text chunking consists of dividing a text in syntactically correlated parts of words. For example, the sentence
 He reckons the current account deficit will narrow to only # 1.8 billion in September . can be divided as follows:
[NP He ] [VP reckons ] [NP the current account deficit ] [VP will narrow ] [PP to ] [NP only # 1.8 billion ]
[PP in ] [NP September ] .

Text chunking is an intermediate step towards full parsing. It was the shared task for CoNLL-2000. Training and test
data for this task is available. This data consists of the same partitions of the Wall Street Journal corpus (WSJ)
as the widely used data for noun phrase chunking: sections 15-18 as training data (211727 tokens) and section 20 as
test data (47377 tokens). The annotation of the data has been derived from the WSJ corpus by a program written by
Sabine Buchholz from Tilburg University, The Netherlands.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### conll2000

- **Size of downloaded dataset files:** 3.32 MB
- **Size of the generated dataset:** 6.25 MB
- **Total amount of disk used:** 9.57 MB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{
    "chunk_tags": [11, 13, 11, 12, 21, 22, 22, 22, 22, 11, 12, 12, 17, 11, 12, 13, 11, 0, 1, 13, 11, 11, 0, 21, 22, 22, 11, 12, 12, 13, 11, 12, 12, 11, 12, 12, 0],
    "id": "0",
    "pos_tags": [19, 14, 11, 19, 39, 27, 37, 32, 34, 11, 15, 19, 14, 19, 22, 14, 20, 5, 15, 14, 19, 19, 5, 34, 32, 34, 11, 15, 19, 14, 20, 9, 20, 24, 15, 22, 6],
    "tokens": "[\"Confidence\", \"in\", \"the\", \"pound\", \"is\", \"widely\", \"expected\", \"to\", \"take\", \"another\", \"sharp\", \"dive\", \"if\", \"trade\", \"figur..."
}
```

### Data Fields

The data fields are the same among all splits.

#### conll2000
- `id`: a `string` feature.
- `tokens`: a `list` of `string` features.
- `pos_tags`: a `list` of classification labels, with possible values including `''` (0), `#` (1), `$` (2), `(` (3), `)` (4).
- `chunk_tags`: a `list` of classification labels, with possible values including `O` (0), `B-ADJP` (1), `I-ADJP` (2), `B-ADVP` (3), `I-ADVP` (4).

### Data Splits

|  name   |train|test|
|---------|----:|---:|
|conll2000| 8937|2013|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@inproceedings{tksbuchholz2000conll,
   author     = "Tjong Kim Sang, Erik F. and Sabine Buchholz",
   title      = "Introduction to the CoNLL-2000 Shared Task: Chunking",
   editor     = "Claire Cardie and Walter Daelemans and Claire
                 Nedellec and Tjong Kim Sang, Erik",
   booktitle  = "Proceedings of CoNLL-2000 and LLL-2000",
   publisher  = "Lisbon, Portugal",
   pages      = "127--132",
   year       = "2000"
}

```


### Contributions

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