
# NLU Evaluation Data - English and German
A labeled English **and German** language multi-domain dataset (21 domains) with 25K user utterances for human-robot interaction.

This dataset is collected and annotated for evaluating NLU services and platforms.
The detailed paper on this dataset can be found at arXiv.org:
[Benchmarking Natural Language Understanding Services for building Conversational Agents](https://arxiv.org/abs/1903.05566)

The dataset builds on the annotated data of the [xliuhw/NLU-Evaluation-Data](https://github.com/xliuhw/NLU-Evaluation-Data)
repository. We have added an additional column (`answer_de`)
by translating the texts in column `answer` into German.
The translation was made with [DeepL](https://www.deepl.com/translator).

## Creator

This data set was compiled and open sourced by [Philip May](https://may.la/)
of [Deutsche Telekom](https://www.telekom.de/).

## Labels
The columns `scenario` and `intent` can be used for classification tasks.
However, we recommend to use even more fine-grained labels.
For this purpose, a new label can be derived by concatenating `scenario` and `intent`.
For example, this would turn "alarm" and "set" into "alarm_set".

## Dataset Quirks
The original dataset contains some `NaN` values in the `answer` column.
This means that there are also `NaN` values in the translations (`answer_de` column).
These rows should be filtered.

The dataset also contains duplicate values.

## Copyright
Copyright (c) the authors of [xliuhw/NLU-Evaluation-Data](https://github.com/xliuhw/NLU-Evaluation-Data)\
Copyright (c) 2022 [Philip May](https://may.la/)

All data is released under the
[Creative Commons Attribution 4.0 International License (CC BY 4.0)](http://creativecommons.org/licenses/by/4.0/).

task_categories:text-classification task_ids:intent-classification multilinguality:multilingual size_categories:10K<n<100K source_datasets:extended|nlu_evaluation_data language:en language:de license:cc-by-4.0 arxiv:1903.05566 region:us
{"language": ["en", "de"], "license": "cc-by-4.0", "multilinguality": ["multilingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["extended|nlu_evaluation_data"], "task_categories": ["text-classification"], "task_ids": ["intent-classification"]}
TAGS
#task_categories-text-classification #task_ids-intent-classification #multilinguality-multilingual #size_categories-10K<n<100K #source_datasets-extended|nlu_evaluation_data #language-English #language-German #license-cc-by-4.0 #arxiv-1903.05566 #region-us 


# NLU Evaluation Data - English and German
A labeled English and German language multi-domain dataset (21 domains) with 25K user utterances for human-robot interaction.

This dataset is collected and annotated for evaluating NLU services and platforms.
The detailed paper on this dataset can be found at URL:
Benchmarking Natural Language Understanding Services for building Conversational Agents

The dataset builds on the annotated data of the xliuhw/NLU-Evaluation-Data
repository. We have added an additional column ('answer_de')
by translating the texts in column 'answer' into German.
The translation was made with DeepL.

## Creator

This data set was compiled and open sourced by Philip May
of Deutsche Telekom.

## Labels
The columns 'scenario' and 'intent' can be used for classification tasks.
However, we recommend to use even more fine-grained labels.
For this purpose, a new label can be derived by concatenating 'scenario' and 'intent'.
For example, this would turn "alarm" and "set" into "alarm_set".

## Dataset Quirks
The original dataset contains some 'NaN' values in the 'answer' column.
This means that there are also 'NaN' values in the translations ('answer_de' column).
These rows should be filtered.

The dataset also contains duplicate values.

## Copyright
Copyright (c) the authors of xliuhw/NLU-Evaluation-Data\
Copyright (c) 2022 Philip May

All data is released under the
Creative Commons Attribution 4.0 International License (CC BY 4.0).

# NLU Evaluation Data - English and German
A labeled English and German language multi-domain dataset (21 domains) with 25K user utterances for human-robot interaction.

This dataset is collected and annotated for evaluating NLU services and platforms.
The detailed paper on this dataset can be found at URL:
Benchmarking Natural Language Understanding Services for building Conversational Agents

The dataset builds on the annotated data of the xliuhw/NLU-Evaluation-Data
repository. We have added an additional column ('answer_de')
by translating the texts in column 'answer' into German.
The translation was made with DeepL. ## Creator

This data set was compiled and open sourced by Philip May
of Deutsche Telekom. ## Labels
The columns 'scenario' and 'intent' can be used for classification tasks.
However, we recommend to use even more fine-grained labels.
For this purpose, a new label can be derived by concatenating 'scenario' and 'intent'.
For example, this would turn "alarm" and "set" into "alarm_set". ## Dataset Quirks
The original dataset contains some 'NaN' values in the 'answer' column.
This means that there are also 'NaN' values in the translations ('answer_de' column).
These rows should be filtered.

The dataset also contains duplicate values. ## Copyright
Copyright (c) the authors of xliuhw/NLU-Evaluation-Data\
Copyright (c) 2022 Philip May

All data is released under the
Creative Commons Attribution 4.0 International License (CC BY 4.0).
TAGS
#task_categories-text-classification #task_ids-intent-classification #multilinguality-multilingual #size_categories-10K<n<100K #source_datasets-extended|nlu_evaluation_data #language-English #language-German #license-cc-by-4.0 #arxiv-1903.05566 #region-us 
 # NLU Evaluation Data - English and German
A labeled English and German language multi-domain dataset (21 domains) with 25K user utterances for human-robot interaction.

This dataset is collected and annotated for evaluating NLU services and platforms.
The detailed paper on this dataset can be found at URL:
Benchmarking Natural Language Understanding Services for building Conversational Agents

The dataset builds on the annotated data of the xliuhw/NLU-Evaluation-Data
repository. We have added an additional column ('answer_de')
by translating the texts in column 'answer' into German.
The translation was made with DeepL. ## Creator

This data set was compiled and open sourced by Philip May
of Deutsche Telekom. ## Labels
The columns 'scenario' and 'intent' can be used for classification tasks.
However, we recommend to use even more fine-grained labels.
For this purpose, a new label can be derived by concatenating 'scenario' and 'intent'.
For example, this would turn "alarm" and "set" into "alarm_set". ## Dataset Quirks
The original dataset contains some 'NaN' values in the 'answer' column.
This means that there are also 'NaN' values in the translations ('answer_de' column).
These rows should be filtered.

The dataset also contains duplicate values. ## Copyright
Copyright (c) the authors of xliuhw/NLU-Evaluation-Data\
Copyright (c) 2022 Philip May

All data is released under the
Creative Commons Attribution 4.0 International License (CC BY 4.0).
passage: TAGS
#task_categories-text-classification #task_ids-intent-classification #multilinguality-multilingual #size_categories-10K<n<100K #source_datasets-extended|nlu_evaluation_data #language-English #language-German #license-cc-by-4.0 #arxiv-1903.05566 #region-us 
# NLU Evaluation Data - English and German
A labeled English and German language multi-domain dataset (21 domains) with 25K user utterances for human-robot interaction.

This dataset is collected and annotated for evaluating NLU services and platforms.
The detailed paper on this dataset can be found at URL:
Benchmarking Natural Language Understanding Services for building Conversational Agents

The dataset builds on the annotated data of the xliuhw/NLU-Evaluation-Data
repository. We have added an additional column ('answer_de')
by translating the texts in column 'answer' into German.
The translation was made with DeepL.## Creator

This data set was compiled and open sourced by Philip May
of Deutsche Telekom.## Labels
The columns 'scenario' and 'intent' can be used for classification tasks.
However, we recommend to use even more fine-grained labels.
For this purpose, a new label can be derived by concatenating 'scenario' and 'intent'.
For example, this would turn "alarm" and "set" into "alarm_set".## Dataset Quirks
The original dataset contains some 'NaN' values in the 'answer' column.
This means that there are also 'NaN' values in the translations ('answer_de' column).
These rows should be filtered.

The dataset also contains duplicate values.## Copyright
Copyright (c) the authors of xliuhw/NLU-Evaluation-Data\
Copyright (c) 2022 Philip May

All data is released under the
Creative Commons Attribution 4.0 International License (CC BY 4.0).