| | --- |
| | 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 |
| | --- |
| | # 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. |
