Datasets:
multi_booked

	---
	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.