参考：
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:disaster_response_messages')
- 说明：
This dataset contains 30,000 messages drawn from events including an earthquake in Haiti in 2010, an earthquake in Chile in 2010, floods in Pakistan in 2010, super-storm Sandy in the U.S.A. in 2012, and news articles spanning a large number of years and 100s of different disasters.
The data has been encoded with 36 different categories related to disaster response and has been stripped of messages with sensitive information in their entirety.
Upon release, this is the featured dataset of a new Udacity course on Data Science and the AI4ALL summer school and is especially utile for text analytics and natural language processing (NLP) tasks and models.
The input data in this job contains thousands of untranslated disaster-related messages and their English translations.
- 许可：无已知许可
- 版本：0.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
2629 |
'train' |
21046 |
'validation' |
2573 |
- 特征：
{
"split": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"message": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"genre": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"related": {
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"names": [
"false",
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"maybe"
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"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"PII": {
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"request": {
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"id": null,
"_type": "ClassLabel"
},
"offer": {
"dtype": "int8",
"id": null,
"_type": "Value"
},
"aid_related": {
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"names": [
"false",
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],
"names_file": null,
"id": null,
"_type": "ClassLabel"
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"medical_help": {
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"names": [
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"food": {
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"shelter": {
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"clothing": {
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"money": {
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"missing_people": {
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"refugees": {
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"death": {
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"other_aid": {
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"buildings": {
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"electricity": {
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"tools": {
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"hospitals": {
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"shops": {
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"aid_centers": {
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"other_infrastructure": {
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"weather_related": {
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"floods": {
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"storm": {
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"fire": {
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"earthquake": {
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"cold": {
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"other_weather": {
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"direct_report": {
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}