# Dataset Card for HighlightSum Corpus [Single Dataset Comprising of AMI, SamSUM & DialogSUM for Brief Summarization of Text]
## Dataset Description
### Links
- **AMI:** https://huggingface.co/datasets/knkarthick/AMI
- **DialogSUM:** https://github.com/cylnlp/dialogsum
- **SamSUM:** https://huggingface.co/datasets/knkarthick/samsum
- **Point of Contact:** https://huggingface.co/knkarthick

### Dataset Summary
HighlightSUM is collection of large-scale dialogue summarization dataset from AMI, SamSUM & DialogSUM, consisting of 31,108 dialogues with corresponding manually labeled summaries.
### Languages
English

## Dataset Structure
### Data Instances
HighlightSum is a large-scale dialogue summarization dataset collection, consisting of 31,108 dialogues split into train, test and validation.

The first instance in the training set:
{'id': 'train_0', 
'summary': "Mr. Smith's getting a check-up, and Doctor Hawkins advises him to have one every year. Hawkins'll give some information about their classes and medications to help Mr. Smith quit smoking.", 
'dialogue': "#Person1#: Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today?\n#Person2#: I found it would be a good idea to get a check-up.\n#Person1#: Yes, well, you haven't had one for 5 years. You should have one every year.\n#Person2#: I know. I figure as long as there is nothing wrong, why go see the doctor?\n#Person1#: Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good.\n#Person2#: Ok.\n#Person1#: Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith?\n#Person2#: Yes.\n#Person1#: Smoking is the leading cause of lung cancer and heart disease, you know. You really should quit.\n#Person2#: I've tried hundreds of times, but I just can't seem to kick the habit.\n#Person1#: Well, we have classes and some medications that might help. I'll give you more information before you leave.\n#Person2#: Ok, thanks doctor."}

### Data Fields
- dialogue: text of dialogue.
- summary: human written summary of the dialogue.
- id: unique file id of an example.

### Data Splits
- train: 27401
- val: 1360
- test: 2347

## Dataset Creation
### Curation Rationale
Collection of AMI, SamSUM & DialogSUM Datasets.
### Who are the source language producers?
linguists
### Who are the annotators?
language experts

## Licensing Information
non-commercial licence: MIT
## Citation Information
Refer the above links for Credits & Citations.
task_categories:summarization annotations_creators:expert-generated language_creators:expert-generated multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:en license:mit region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["summarization"], "task_ids": [], "pretty_name": "HighlightSum Corpus"}
TAGS
#task_categories-summarization #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #region-us 

# Dataset Card for HighlightSum Corpus [Single Dataset Comprising of AMI, SamSUM & DialogSUM for Brief Summarization of Text]
## Dataset Description
### Links
- AMI: URL
- DialogSUM: URL
- SamSUM: URL
- Point of Contact: URL

### Dataset Summary
HighlightSUM is collection of large-scale dialogue summarization dataset from AMI, SamSUM & DialogSUM, consisting of 31,108 dialogues with corresponding manually labeled summaries.
### Languages
English

## Dataset Structure
### Data Instances
HighlightSum is a large-scale dialogue summarization dataset collection, consisting of 31,108 dialogues split into train, test and validation.

The first instance in the training set:
{'id': 'train_0', 
'summary': "Mr. Smith's getting a check-up, and Doctor Hawkins advises him to have one every year. Hawkins'll give some information about their classes and medications to help Mr. Smith quit smoking.", 
'dialogue': "#Person1#: Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today?\n#Person2#: I found it would be a good idea to get a check-up.\n#Person1#: Yes, well, you haven't had one for 5 years. You should have one every year.\n#Person2#: I know. I figure as long as there is nothing wrong, why go see the doctor?\n#Person1#: Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good.\n#Person2#: Ok.\n#Person1#: Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith?\n#Person2#: Yes.\n#Person1#: Smoking is the leading cause of lung cancer and heart disease, you know. You really should quit.\n#Person2#: I've tried hundreds of times, but I just can't seem to kick the habit.\n#Person1#: Well, we have classes and some medications that might help. I'll give you more information before you leave.\n#Person2#: Ok, thanks doctor."}

### Data Fields
- dialogue: text of dialogue.
- summary: human written summary of the dialogue.
- id: unique file id of an example.

### Data Splits
- train: 27401
- val: 1360
- test: 2347

## Dataset Creation
### Curation Rationale
Collection of AMI, SamSUM & DialogSUM Datasets.
### Who are the source language producers?
linguists
### Who are the annotators?
language experts

## Licensing Information
non-commercial licence: MIT

Refer the above links for Credits & Citations.
# Dataset Card for HighlightSum Corpus [Single Dataset Comprising of AMI, SamSUM & DialogSUM for Brief Summarization of Text] ## Dataset Description ### Links
- AMI: URL
- DialogSUM: URL
- SamSUM: URL
- Point of Contact: URL ### Dataset Summary
HighlightSUM is collection of large-scale dialogue summarization dataset from AMI, SamSUM & DialogSUM, consisting of 31,108 dialogues with corresponding manually labeled summaries. ### Languages
English ## Dataset Structure ### Data Instances
HighlightSum is a large-scale dialogue summarization dataset collection, consisting of 31,108 dialogues split into train, test and validation.

The first instance in the training set:
{'id': 'train_0', 
'summary': "Mr. Smith's getting a check-up, and Doctor Hawkins advises him to have one every year. Hawkins'll give some information about their classes and medications to help Mr. Smith quit smoking.", 
'dialogue': "#Person1#: Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today?\n#Person2#: I found it would be a good idea to get a check-up.\n#Person1#: Yes, well, you haven't had one for 5 years. You should have one every year.\n#Person2#: I know. I figure as long as there is nothing wrong, why go see the doctor?\n#Person1#: Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good.\n#Person2#: Ok.\n#Person1#: Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith?\n#Person2#: Yes.\n#Person1#: Smoking is the leading cause of lung cancer and heart disease, you know. You really should quit.\n#Person2#: I've tried hundreds of times, but I just can't seem to kick the habit.\n#Person1#: Well, we have classes and some medications that might help. I'll give you more information before you leave.\n#Person2#: Ok, thanks doctor."} ### Data Fields
- dialogue: text of dialogue.
- summary: human written summary of the dialogue.
- id: unique file id of an example. ### Data Splits
- train: 27401
- val: 1360
- test: 2347 ## Dataset Creation ### Curation Rationale
Collection of AMI, SamSUM & DialogSUM Datasets. ### Who are the source language producers?
linguists ### Who are the annotators?
language experts ## Licensing Information
non-commercial licence: MIT

Refer the above links for Credits & Citations.
TAGS
#task_categories-summarization #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #region-us 
 # Dataset Card for HighlightSum Corpus [Single Dataset Comprising of AMI, SamSUM & DialogSUM for Brief Summarization of Text] ## Dataset Description ### Links
- AMI: URL
- DialogSUM: URL
- SamSUM: URL
- Point of Contact: URL ### Dataset Summary
HighlightSUM is collection of large-scale dialogue summarization dataset from AMI, SamSUM & DialogSUM, consisting of 31,108 dialogues with corresponding manually labeled summaries. ### Languages
English ## Dataset Structure ### Data Instances
HighlightSum is a large-scale dialogue summarization dataset collection, consisting of 31,108 dialogues split into train, test and validation.

The first instance in the training set:
{'id': 'train_0', 
'summary': "Mr. Smith's getting a check-up, and Doctor Hawkins advises him to have one every year. Hawkins'll give some information about their classes and medications to help Mr. Smith quit smoking.", 
'dialogue': "#Person1#: Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today?\n#Person2#: I found it would be a good idea to get a check-up.\n#Person1#: Yes, well, you haven't had one for 5 years. You should have one every year.\n#Person2#: I know. I figure as long as there is nothing wrong, why go see the doctor?\n#Person1#: Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good.\n#Person2#: Ok.\n#Person1#: Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith?\n#Person2#: Yes.\n#Person1#: Smoking is the leading cause of lung cancer and heart disease, you know. You really should quit.\n#Person2#: I've tried hundreds of times, but I just can't seem to kick the habit.\n#Person1#: Well, we have classes and some medications that might help. I'll give you more information before you leave.\n#Person2#: Ok, thanks doctor."} ### Data Fields
- dialogue: text of dialogue.
- summary: human written summary of the dialogue.
- id: unique file id of an example. ### Data Splits
- train: 27401
- val: 1360
- test: 2347 ## Dataset Creation ### Curation Rationale
Collection of AMI, SamSUM & DialogSUM Datasets. ### Who are the source language producers?
linguists ### Who are the annotators?
language experts ## Licensing Information
non-commercial licence: MIT

Refer the above links for Credits & Citations.
passage: TAGS
#task_categories-summarization #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #region-us 
# Dataset Card for HighlightSum Corpus [Single Dataset Comprising of AMI, SamSUM & DialogSUM for Brief Summarization of Text]## Dataset Description### Links
- AMI: URL
- DialogSUM: URL
- SamSUM: URL
- Point of Contact: URL### Dataset Summary
HighlightSUM is collection of large-scale dialogue summarization dataset from AMI, SamSUM & DialogSUM, consisting of 31,108 dialogues with corresponding manually labeled summaries.### Languages
English## Dataset Structure