task_categories:text-classification task_ids:sentiment-classification annotations_creators:expert-generated language_creators:found multilinguality:monolingual size_categories:n<1K source_datasets:original language:ca language:eu license:cc-by-3.0 arxiv:1803.08614 region:us
MultiBooked is a corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification.

The corpora are compiled from hotel reviews taken mainly from booking.com. The corpora are in Kaf/Naf format, which is
an xml-style stand-off format that allows for multiple layers of annotation. Each review was sentence- and
word-tokenized and lemmatized using Freeling for Catalan and ixa-pipes for Basque. Finally, for each language two
annotators annotated opinion holders, opinion targets, and opinion expressions for each review, following the
guidelines set out in the OpeNER project.
@inproceedings{Barnes2018multibooked,
    author={Barnes, Jeremy and Lambert, Patrik and Badia, Toni},
    title={MultiBooked: A corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification},
    booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC'18)},
    year = {2018},
    month = {May},
    date = {7-12},
    address = {Miyazaki, Japan},
    publisher = {European Language Resources Association (ELRA)},
    language = {english}
}
---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
- eu
license:
- cc-by-3.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
paperswithcode_id: multibooked
pretty_name: MultiBooked
dataset_info:
- config_name: ca
  features:
  - name: text
    sequence:
    - name: wid
      dtype: string
    - name: sent
      dtype: string
    - name: para
      dtype: string
    - name: word
      dtype: string
  - name: terms
    sequence:
    - name: tid
      dtype: string
    - name: lemma
      dtype: string
    - name: morphofeat
      dtype: string
    - name: pos
      dtype: string
    - name: target
      sequence: string
  - name: opinions
    sequence:
    - name: oid
      dtype: string
    - name: opinion_holder_target
      sequence: string
    - name: opinion_target_target
      sequence: string
    - name: opinion_expression_polarity
      dtype:
        class_label:
          names:
            '0': StrongNegative
            '1': Negative
            '2': Positive
            '3': StrongPositive
    - name: opinion_expression_target
      sequence: string
  splits:
  - name: train
    num_bytes: 1952731
    num_examples: 567
  download_size: 4429415
  dataset_size: 1952731
- config_name: eu
  features:
  - name: text
    sequence:
    - name: wid
      dtype: string
    - name: sent
      dtype: string
    - name: para
      dtype: string
    - name: word
      dtype: string
  - name: terms
    sequence:
    - name: tid
      dtype: string
    - name: lemma
      dtype: string
    - name: morphofeat
      dtype: string
    - name: pos
      dtype: string
    - name: target
      sequence: string
  - name: opinions
    sequence:
    - name: oid
      dtype: string
    - name: opinion_holder_target
      sequence: string
    - name: opinion_target_target
      sequence: string
    - name: opinion_expression_polarity
      dtype:
        class_label:
          names:
            '0': StrongNegative
            '1': Negative
            '2': Positive
            '3': StrongPositive
    - name: opinion_expression_target
      sequence: string
  splits:
  - name: train
    num_bytes: 1175816
    num_examples: 343
  download_size: 4429415
  dataset_size: 1175816
config_names:
- ca
- eu
---

# Dataset Card for MultiBooked

## 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:** http://hdl.handle.net/10230/33928
- **Repository:** https://github.com/jerbarnes/multibooked
- **Paper:** https://arxiv.org/abs/1803.08614
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

MultiBooked is a corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification.

The corpora are compiled from hotel reviews taken mainly from booking.com. The corpora are in Kaf/Naf format, which is
an xml-style stand-off format that allows for multiple layers of annotation. Each review was sentence- and
word-tokenized and lemmatized using Freeling for Catalan and ixa-pipes for Basque. Finally, for each language two
annotators annotated opinion holders, opinion targets, and opinion expressions for each review, following the
guidelines set out in the OpeNER project.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

Each sub-dataset is monolingual in the languages:
- ca: Catalan
- eu: Basque

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

- `text`: layer of the original text.
  - `wid`: list of word IDs for each word within the example.
  - `sent`: list of sentence IDs for each sentence within the example.
  - `para`: list of paragraph IDs for each paragraph within the example.
  - `word`: list of words.
- `terms`: layer of the terms resulting from the analysis of the original text (lemmatization, morphological,
  PoS tagging)
  - `tid`: list of term IDs for each term within the example.
  - `lemma`: list of lemmas.
  - `morphofeat`: list of morphological features.
  - `pos`: list of PoS tags.
  - `target`: list of sublists of the corresponding word IDs (normally, the sublists contain only one element,
    in a one-to-one correspondence between words and terms).
- `opinions`: layer of the opinions in the text.
  - `oid`: list of opinion IDs
  - `opinion_holder_target`: list of sublists of the corresponding term IDs that span the opinion holder.
  - `opinion_target_target`: list of sublists of the corresponding term IDs that span the opinion target.
  - `opinion_expression_polarity`: list of the opinion expression polarities. The polarity can take one of the values:
    `StrongNegative`, `Negative`, `Positive`, or `StrongPositive`.
  - `opinion_expression_target`: list of sublists of the corresponding term IDs that span the opinion expression.

### Data Splits

[More Information Needed]

## 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

Dataset is under the [CC-BY 3.0](https://creativecommons.org/licenses/by/3.0/) license.

### Citation Information

```
@inproceedings{Barnes2018multibooked,
    author={Barnes, Jeremy and Lambert, Patrik and Badia, Toni},
    title={MultiBooked: A corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification},
    booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC'18)},
    year = {2018},
    month = {May},
    date = {7-12},
    address = {Miyazaki, Japan},
    publisher = {European Language Resources Association (ELRA)},
    language = {english}
}
```

### Contributions

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