Datasets:
Tasks:
Text Classification
Sub-tasks:
intent-classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
Tags:
License:
Commit
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2f4bf07
1
Parent(s):
52dc8b2
Convert dataset to Parquet
Browse filesConvert dataset to Parquet.
- README.md +10 -5
- country_2020-09-01_2020-09-30/train-00000-of-00001.parquet +3 -0
- dataset_infos.json +54 -1
README.md
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- text-classification
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task_ids:
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- intent-classification
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paperswithcode_id: null
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pretty_name: BingCoronavirusQuerySet
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dataset_info:
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features:
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- name: id
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dtype: int32
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dtype: string
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- name: PopularityScore
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dtype: int32
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config_name: country_2020-09-01_2020-09-30
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splits:
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- name: train
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-
num_bytes:
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num_examples: 317856
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-
download_size:
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dataset_size:
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---
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# Dataset Card for BingCoronavirusQuerySet
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- text-classification
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task_ids:
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- intent-classification
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pretty_name: BingCoronavirusQuerySet
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dataset_info:
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config_name: country_2020-09-01_2020-09-30
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features:
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- name: id
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dtype: int32
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dtype: string
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- name: PopularityScore
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dtype: int32
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splits:
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- name: train
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num_bytes: 22052194
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num_examples: 317856
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download_size: 6768102
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dataset_size: 22052194
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configs:
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- config_name: country_2020-09-01_2020-09-30
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data_files:
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- split: train
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path: country_2020-09-01_2020-09-30/train-*
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default: true
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---
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# Dataset Card for BingCoronavirusQuerySet
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country_2020-09-01_2020-09-30/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:caea2c4420516b33f8d1515bec0686702b94d2c74cdb2ccbd16104d9875e4ee6
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size 6768102
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dataset_infos.json
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{
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{
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"country_2020-09-01_2020-09-30": {
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"description": "This dataset was curated from the Bing search logs (desktop users only) over the period of Jan 1st, 2020 \u2013 (Current Month - 1). Only searches that were issued many times by multiple users were included. The dataset includes queries from all over the world that had an intent related to the Coronavirus or Covid-19. In some cases this intent is explicit in the query itself (e.g., \u201cCoronavirus updates Seattle\u201d), in other cases it is implicit , e.g. \u201cShelter in place\u201d. The implicit intent of search queries (e.g., \u201cToilet paper\u201d) was extracted using random walks on the click graph as outlined in this paper by Microsoft Research. All personal data were removed.\n",
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"citation": "",
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"homepage": "https://github.com/microsoft/BingCoronavirusQuerySet",
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"license": "",
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"features": {
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"id": {
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"dtype": "int32",
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"_type": "Value"
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},
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"Date": {
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"dtype": "string",
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"_type": "Value"
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},
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"Query": {
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"dtype": "string",
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"_type": "Value"
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},
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"IsImplicitIntent": {
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"dtype": "string",
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"_type": "Value"
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},
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"Country": {
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"dtype": "string",
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"_type": "Value"
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},
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"PopularityScore": {
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"dtype": "int32",
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"_type": "Value"
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}
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},
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"builder_name": "bing_coronavirus_query_set",
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"dataset_name": "bing_coronavirus_query_set",
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"config_name": "country_2020-09-01_2020-09-30",
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"version": {
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"version_str": "1.0.0",
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"major": 1,
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"minor": 0,
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"patch": 0
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},
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 22052194,
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"num_examples": 317856,
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"dataset_name": null
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}
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},
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"download_size": 6768102,
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"dataset_size": 22052194,
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"size_in_bytes": 28820296
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}
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}
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