|
--- |
|
annotations_creators: |
|
- other |
|
language_creators: |
|
- other |
|
language: |
|
- en |
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expert-generated license: |
|
- cc-by-nc-sa-4.0 |
|
multilinguality: |
|
- monolingual |
|
size_categories: |
|
- n<1K |
|
source_datasets: |
|
- original |
|
task_categories: |
|
- question-answering |
|
- text-retrieval |
|
- text2text-generation |
|
- other |
|
- translation |
|
- conversational |
|
task_ids: |
|
- extractive-qa |
|
- closed-domain-qa |
|
- utterance-retrieval |
|
- document-retrieval |
|
- closed-domain-qa |
|
- open-book-qa |
|
- closed-book-qa |
|
paperswithcode_id: acronym-identification |
|
pretty_name: Massive E-commerce Dataset for Retail and Insurance domain. |
|
train-eval-index: |
|
- config: nsds |
|
task: token-classification |
|
task_id: entity_extraction |
|
splits: |
|
train_split: train |
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eval_split: test |
|
col_mapping: |
|
sentence: text |
|
label: target |
|
metrics: |
|
- type: nsme-com |
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name: NSME-COM |
|
config: |
|
nsds |
|
tags: |
|
- chatbots |
|
- e-commerce |
|
- retail |
|
- insurance |
|
- consumer |
|
- consumer goods |
|
configs: |
|
- nsds |
|
--- |
|
# Dataset Card for NSME-COM |
|
|
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## Table of Contents |
|
|
|
- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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|
|
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|
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- **Homepage**: [https://huggingface.co/asaxena1990) |
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- **Repository:** [https://huggingface.co/datasets/asaxena1990/NSME-COM) |
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- **Point of Contact:** (Ayushman Dash <[email protected]>, Ankur Saxena <[email protected]>) |
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|
|
- **Size of downloaded dataset files:** 10.86 KB |
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|
|
### Dataset Summary |
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|
|
NSME-COM, the NeuralSpace Massive E-commerce Dataset is a collection of resources for training, evaluating, and analyzing natural language understanding systems. |
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|
|
### Supported Tasks and Leaderboards |
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|
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#### nsds |
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|
|
A manually-curated domain specific dataset by Data Engineers at NeuralSpace for rare E-commerce domains such as Insurance and Retail for NL researchers and practitioners to evaluate state of the art models [here](https://www.neuralspace.ai/) in 100+ languages. The dataset files are available in JSON format. |
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|
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### Languages |
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|
|
The language data in NSME-COM is in English (BCP-47 `en`) |
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|
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## Dataset Structure |
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|
|
### Data Instances |
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|
|
- **Size of downloaded dataset files:** 10.86 KB |
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|
|
An example of 'test' looks as follows. |
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|
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``` { |
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"text": "is it good to add roadside assistance?", |
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"intent": "Add", |
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"type": "Test" |
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} |
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``` |
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|
|
An example of 'train' looks as follows. |
|
|
|
```{ |
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"text": "how can I add my spouse as a nominee?", |
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"intent": "Add", |
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"type": "Train" |
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}, |
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``` |
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|
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### Data Fields |
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|
|
The data fields are the same among all splits. |
|
|
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#### nsds |
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|
|
- `text`: a `string` feature. |
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- `intent`: a `string` feature. |
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- `type`: a classification label, with possible values including `train` or `test`. |
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|
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### Data Splits |
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|
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#### nsds |
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| |train|test| |
|
|----|----:|---:| |
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|nsds| 1725| 406| |
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|
|
### Contributions |
|
Ankur Saxena ([email protected]) |
