
# Dataset Card for "sem_eval_2010_task_8"

## 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:** [https://semeval2.fbk.eu/semeval2.php?location=tasks&taskid=11](https://semeval2.fbk.eu/semeval2.php?location=tasks&taskid=11)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 1.96 MB
- **Size of the generated dataset:** 1.42 MB
- **Total amount of disk used:** 3.38 MB

### Dataset Summary

The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals.
The task was designed to compare different approaches to semantic relation classification
and to provide a standard testbed for future research.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### default

- **Size of downloaded dataset files:** 1.96 MB
- **Size of the generated dataset:** 1.42 MB
- **Total amount of disk used:** 3.38 MB

An example of 'train' looks as follows.
```
{
    "relation": 3,
    "sentence": "The system as described above has its greatest application in an arrayed <e1>configuration</e1> of antenna <e2>elements</e2>."
}
```

### Data Fields

The data fields are the same among all splits.

#### default
- `sentence`: a `string` feature.
- `relation`: a classification label, with possible values including `Cause-Effect(e1,e2)` (0), `Cause-Effect(e2,e1)` (1), `Component-Whole(e1,e2)` (2), `Component-Whole(e2,e1)` (3), `Content-Container(e1,e2)` (4).

### Data Splits

| name  |train|test|
|-------|----:|---:|
|default| 8000|2717|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@inproceedings{hendrickx-etal-2010-semeval,
    title = "{S}em{E}val-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals",
    author = "Hendrickx, Iris  and
      Kim, Su Nam  and
      Kozareva, Zornitsa  and
      Nakov, Preslav  and
      {'O} S{'e}aghdha, Diarmuid  and
      Pad{'o}, Sebastian  and
      Pennacchiotti, Marco  and
      Romano, Lorenza  and
      Szpakowicz, Stan",
    booktitle = "Proceedings of the 5th International Workshop on Semantic Evaluation",
    month = jul,
    year = "2010",
    address = "Uppsala, Sweden",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/S10-1006",
    pages = "33--38",
}

```


### Contributions

Thanks to [@JoelNiklaus](https://github.com/JoelNiklaus) for adding this dataset.
language:en region:us
{"language": ["en"], "paperswithcode_id": "semeval-2010-task-8", "pretty_name": "SemEval-2010 Task 8", "dataset_info": {"features": [{"name": "sentence", "dtype": "string"}, {"name": "relation", "dtype": {"class_label": {"names": {"0": "Cause-Effect(e1,e2)", "1": "Cause-Effect(e2,e1)", "2": "Component-Whole(e1,e2)", "3": "Component-Whole(e2,e1)", "4": "Content-Container(e1,e2)", "5": "Content-Container(e2,e1)", "6": "Entity-Destination(e1,e2)", "7": "Entity-Destination(e2,e1)", "8": "Entity-Origin(e1,e2)", "9": "Entity-Origin(e2,e1)", "10": "Instrument-Agency(e1,e2)", "11": "Instrument-Agency(e2,e1)", "12": "Member-Collection(e1,e2)", "13": "Member-Collection(e2,e1)", "14": "Message-Topic(e1,e2)", "15": "Message-Topic(e2,e1)", "16": "Product-Producer(e1,e2)", "17": "Product-Producer(e2,e1)", "18": "Other"}}}}], "splits": [{"name": "train", "num_bytes": 1054352, "num_examples": 8000}, {"name": "test", "num_bytes": 357075, "num_examples": 2717}], "download_size": 1964087, "dataset_size": 1411427}, "train-eval-index": [{"config": "default", "task": "text-classification", "task_id": "multi_class_classification", "splits": {"train_split": "train", "eval_split": "test"}, "col_mapping": {"sentence": "text", "relation": "target"}, "metrics": [{"type": "accuracy", "name": "Accuracy"}, {"type": "f1", "name": "F1 macro", "args": {"average": "macro"}}, {"type": "f1", "name": "F1 micro", "args": {"average": "micro"}}, {"type": "f1", "name": "F1 weighted", "args": {"average": "weighted"}}, {"type": "precision", "name": "Precision macro", "args": {"average": "macro"}}, {"type": "precision", "name": "Precision micro", "args": {"average": "micro"}}, {"type": "precision", "name": "Precision weighted", "args": {"average": "weighted"}}, {"type": "recall", "name": "Recall macro", "args": {"average": "macro"}}, {"type": "recall", "name": "Recall micro", "args": {"average": "micro"}}, {"type": "recall", "name": "Recall weighted", "args": {"average": "weighted"}}]}]}
TAGS
#language-English #region-us 

Dataset Card for "sem\_eval\_2010\_task\_8"
===========================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information
	+ Contributions


Dataset Description
-------------------


* Homepage: URL
* Repository:
* Paper:
* Point of Contact:
* Size of downloaded dataset files: 1.96 MB
* Size of the generated dataset: 1.42 MB
* Total amount of disk used: 3.38 MB


### Dataset Summary


The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals.
The task was designed to compare different approaches to semantic relation classification
and to provide a standard testbed for future research.


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### default


* Size of downloaded dataset files: 1.96 MB
* Size of the generated dataset: 1.42 MB
* Total amount of disk used: 3.38 MB


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### default


* 'sentence': a 'string' feature.
* 'relation': a classification label, with possible values including 'Cause-Effect(e1,e2)' (0), 'Cause-Effect(e2,e1)' (1), 'Component-Whole(e1,e2)' (2), 'Component-Whole(e2,e1)' (3), 'Content-Container(e1,e2)' (4).


### Data Splits



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


### Contributions


Thanks to @JoelNiklaus for adding this dataset.



### Dataset Summary


The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals.
The task was designed to compare different approaches to semantic relation classification
and to provide a standard testbed for future research. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### default


* Size of downloaded dataset files: 1.96 MB
* Size of the generated dataset: 1.42 MB
* Total amount of disk used: 3.38 MB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### default


* 'sentence': a 'string' feature.
* 'relation': a classification label, with possible values including 'Cause-Effect(e1,e2)' (0), 'Cause-Effect(e2,e1)' (1), 'Component-Whole(e1,e2)' (2), 'Component-Whole(e2,e1)' (3), 'Content-Container(e1,e2)' (4). ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @JoelNiklaus for adding this dataset.
TAGS
#language-English #region-us 
 ### Dataset Summary


The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals.
The task was designed to compare different approaches to semantic relation classification
and to provide a standard testbed for future research. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### default


* Size of downloaded dataset files: 1.96 MB
* Size of the generated dataset: 1.42 MB
* Total amount of disk used: 3.38 MB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### default


* 'sentence': a 'string' feature.
* 'relation': a classification label, with possible values including 'Cause-Effect(e1,e2)' (0), 'Cause-Effect(e2,e1)' (1), 'Component-Whole(e1,e2)' (2), 'Component-Whole(e2,e1)' (3), 'Content-Container(e1,e2)' (4). ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @JoelNiklaus for adding this dataset.
passage: TAGS
#language-English #region-us 
### Dataset Summary


The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals.
The task was designed to compare different approaches to semantic relation classification
and to provide a standard testbed for future research.### Supported Tasks and Leaderboards### Languages


Dataset Structure
-----------------### Data Instances#### default


* Size of downloaded dataset files: 1.96 MB
* Size of the generated dataset: 1.42 MB
* Total amount of disk used: 3.38 MB


An example of 'train' looks as follows.### Data Fields


The data fields are the same among all splits.#### default


* 'sentence': a 'string' feature.
* 'relation': a classification label, with possible values including 'Cause-Effect(e1,e2)' (0), 'Cause-Effect(e2,e1)' (1), 'Component-Whole(e1,e2)' (2), 'Component-Whole(e2,e1)' (3), 'Content-Container(e1,e2)' (4).### Data Splits



Dataset Creation
----------------### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------### Social Impact of Dataset### Discussion of Biases### Other Known Limitations


Additional Information
----------------------### Dataset Curators### Licensing Information### Contributions


Thanks to @JoelNiklaus for adding this dataset.