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---
dataset_info:
- config_name: ar
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 8956876
    num_examples: 28041
  download_size: 4304971
  dataset_size: 8956876
- config_name: bo
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 9493216
    num_examples: 29173
  download_size: 4485808
  dataset_size: 9493216
- config_name: cl
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
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  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 8677965
    num_examples: 27136
  download_size: 4102005
  dataset_size: 8677965
- config_name: co
  features:
  - name: id
    dtype: int64
  - name: query
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  - name: docid
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  - name: docid_text
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  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
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  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
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    num_examples: 30770
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- config_name: cr
  features:
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  - name: query
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  - name: docid
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  - name: query_date
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  - name: answer_date
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  - name: match_score
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  - name: expanded_search
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  splits:
  - name: train
    num_bytes: 9216038
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- config_name: cu
  features:
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  - name: query
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  - name: query_date
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  - name: answer_date
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  - name: match_score
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  - name: expanded_search
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  splits:
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    num_examples: 26088
  download_size: 4034287
  dataset_size: 8405344
- config_name: do
  features:
  - name: id
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  - name: query
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  - name: docid
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  - name: docid_text
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  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
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  - name: expanded_search
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  - name: answer_type
    dtype: string
  splits:
  - name: train
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  download_size: 5109811
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- config_name: ec
  features:
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  - name: query
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  - name: query_date
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  splits:
  - name: train
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    num_examples: 32888
  download_size: 5217204
  dataset_size: 10801249
- config_name: es
  features:
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    dtype: int64
  - name: query
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  - name: docid
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  - name: docid_text
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  - name: query_date
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  - name: answer_date
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  - name: match_score
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  - name: expanded_search
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  - name: answer_type
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  splits:
  - name: train
    num_bytes: 9542239
    num_examples: 29745
  download_size: 4614770
  dataset_size: 9542239
- config_name: gt
  features:
  - name: id
    dtype: int64
  - name: query
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  - name: docid
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  - name: docid_text
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  - name: query_date
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  - name: answer_date
    dtype: date32
  - name: match_score
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  - name: expanded_search
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  - name: answer_type
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  splits:
  - name: train
    num_bytes: 8720445
    num_examples: 27116
  download_size: 4162359
  dataset_size: 8720445
- config_name: hn
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
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  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
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  - name: expanded_search
    dtype: bool
  - name: answer_type
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  splits:
  - name: train
    num_bytes: 10279011
    num_examples: 31610
  download_size: 5026318
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- config_name: mx
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 12973900
    num_examples: 39470
  download_size: 6287094
  dataset_size: 12973900
- config_name: ni
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
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  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 10710292
    num_examples: 33005
  download_size: 5251699
  dataset_size: 10710292
- config_name: pa
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 9980751
    num_examples: 30753
  download_size: 4888604
  dataset_size: 9980751
- config_name: pe
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
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  - name: expanded_search
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  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 9853314
    num_examples: 30595
  download_size: 4597604
  dataset_size: 9853314
- config_name: pr
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
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  - name: answer_date
    dtype: date32
  - name: match_score
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  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 10434111
    num_examples: 32224
  download_size: 5134095
  dataset_size: 10434111
- config_name: py
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
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  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 9500315
    num_examples: 29391
  download_size: 4591125
  dataset_size: 9500315
- config_name: sv
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 10040032
    num_examples: 30915
  download_size: 4908064
  dataset_size: 10040032
- config_name: us
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 8613241
    num_examples: 26993
  download_size: 3876126
  dataset_size: 8613241
- config_name: uy
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 8171757
    num_examples: 25620
  download_size: 4038290
  dataset_size: 8171757
- config_name: ve
  features:
  - name: id
    dtype: int64
  - name: query
    dtype: string
  - name: docid
    dtype: string
  - name: docid_text
    dtype: string
  - name: query_date
    dtype: date32
  - name: answer_date
    dtype: date32
  - name: match_score
    dtype: float32
  - name: expanded_search
    dtype: bool
  - name: answer_type
    dtype: string
  splits:
  - name: train
    num_bytes: 10378716
    num_examples: 31952
  download_size: 4999975
  dataset_size: 10378716
configs:
- config_name: ar
  data_files:
  - split: train
    path: ar/train-*
- config_name: bo
  data_files:
  - split: train
    path: bo/train-*
- config_name: cl
  data_files:
  - split: train
    path: cl/train-*
- config_name: co
  data_files:
  - split: train
    path: co/train-*
- config_name: cr
  data_files:
  - split: train
    path: cr/train-*
- config_name: cu
  data_files:
  - split: train
    path: cu/train-*
- config_name: do
  data_files:
  - split: train
    path: do/train-*
- config_name: ec
  data_files:
  - split: train
    path: ec/train-*
- config_name: es
  data_files:
  - split: train
    path: es/train-*
- config_name: gt
  data_files:
  - split: train
    path: gt/train-*
- config_name: hn
  data_files:
  - split: train
    path: hn/train-*
- config_name: mx
  data_files:
  - split: train
    path: mx/train-*
- config_name: ni
  data_files:
  - split: train
    path: ni/train-*
- config_name: pa
  data_files:
  - split: train
    path: pa/train-*
- config_name: pe
  data_files:
  - split: train
    path: pe/train-*
- config_name: pr
  data_files:
  - split: train
    path: pr/train-*
- config_name: py
  data_files:
  - split: train
    path: py/train-*
- config_name: sv
  data_files:
  - split: train
    path: sv/train-*
- config_name: us
  data_files:
  - split: train
    path: us/train-*
- config_name: uy
  data_files:
  - split: train
    path: uy/train-*
- config_name: ve
  data_files:
  - split: train
    path: ve/train-*
---

# Dataset Card for [More Information Needed]

<!-- Provide a quick summary of the dataset. -->

This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).

## Dataset Details

### Dataset Description

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- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]

### Dataset Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

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### Direct Use

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### Out-of-Scope Use

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## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

### Data Instances

<!-- Provide an JSON-formatted example and brief description of a typical instance in the dataset. If available, provide a link to further examples.

```
{
  'example_field': ...,
  ...
}
```

Provide any additional information that is not covered in the other sections about the data here. In particular describe any relationships between data points and if these relationships are made explicit. -->

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### Data Fields

- `id`: query id
- `query`: query text
- `docid`: relevant document id in the corpus
- `docid_text`: relevant document text
- `query_date`: date the query was extracted
- `answer_date`: date the answer was extracted
- `match_score`: the longest string in the SERP answer that is a substring of the matched document text, as a ratio of the length of the SERP answer
- `expanded_search`: if the SERP returned a message indicating that the search was "expanded" with additional results ("se incluyen resultados de...")
- `answer_type`: type of answer extracted (`feat_snippet`, featured snippets, are the most important)

<!-- Note that the descriptions can be initialized with the **Show Markdown Data Fields** output of the [Datasets Tagging app](https://huggingface.co/spaces/huggingface/datasets-tagging), you will then only need to refine the generated descriptions. -->



### Data Splits

<!-- Describe and name the splits in the dataset if there are more than one.

Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g. if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here.

Provide the sizes of each split. As appropriate, provide any descriptive statistics for the features, such as average length.  For example:

|                         | train | validation | test |
|-------------------------|------:|-----------:|-----:|
| Input Sentences         |       |            |      |
| Average Sentence Length |       |            |      |
-->


[More Information Needed]


## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[More Information Needed]

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

[More Information Needed]

#### Who are the source data producers?

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### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->

#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

[More Information Needed]

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[More Information Needed]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

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**APA:**

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## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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