Small tweaks.

README.md

@@ -144,6 +144,8 @@ import datasets
 ds = datasets.load_dataset("allenai/SciRIFF", "4096")
 ```
 
+Code to create the dataset, train models on SciRIFF, and perform evaluation is available at our GitHub repo: https://github.com/allenai/SciRIFF.
+
 ## Dataset details
 
 Each instance in SciRIFF has the following fields:
@@ -151,7 +153,7 @@ Each instance in SciRIFF has the following fields:
 - `input`: Task input (i.e. user message).
 - `output`: Task output (i.e. expected model response).
 - `_instance_id`: A unique id for the instance, formatted like `{task_name}:{split}:{instance_id}`. For instance, `qasa_abstractive_qa:test:182`.
-- `metadata`: Metadata on the task that this particular demonstration is an instance of. More information on the schema for task metadata can be found in the [SciRIFF GitHub repo](https://github.com/allenai/SciRIFF).
+- `metadata`: Task metadata. More information on the schema for task metadata can be found in the [SciRIFF GitHub repo](https://github.com/allenai/SciRIFF).
   - `task_family`: The category to which this task belongs. Options include `summarization`, `ie`, `qa`, `entailment`, and `classification`. Some categories have sub-categories which are largely self-explanatory; see the [repo](https://github.com/allenai/SciRIFF) for more information.
   - `domains`: Scientific field(s) that the task covers. Options include: `clinical_medicine`, `biomedicine`, `chemistry`, `artificial_intelligence`, `materials_science`, and `misc`.
   - `input_context`: Whether the input is a paragraph, full text, etc. Options include: `sentence`, `paragraph`, `multiple_paragraphs` (including full paper text), and `structured` (e.g. code for a LaTex table).
@@ -160,11 +162,11 @@ Each instance in SciRIFF has the following fields:
 
 ## License
 
-SciRIFF is licensed under `ODC-By`.
+SciRIFF is licensed under `ODC-By`. Licenses of the datasets from which SciRIFF is derived are listed [below](#task-provenance).
 
 ## Task provenance
 
-SciRIFF was created by repurposing existing scientific literature understanding datasets. Below we provide information on the source data for each SciRIFF task, including license information on individual datasets where available. Where possible, we leveraged the excellent [BigBIO](https://github.com/bigscience-workshop/biomedical) collection as a starting point, rather than reprocessing datasets from scratch. In the table below, we include the name of the BigBio subset for all tasks included in BigBio; these can be loaded like `datasets.load_dataset(bigbio/{bigbio_subset})`.
+SciRIFF was created by repurposing existing scientific literature understanding datasets. Below we provide information on the source data for each SciRIFF task, including license information on individual datasets where available. Where possible, we leveraged the [BigBIO](https://github.com/bigscience-workshop/biomedical) collection as a starting point, rather than reprocessing datasets from scratch. In the table below, we include the name of the BigBio subset for all tasks available in BigBio; these can be loaded like `datasets.load_dataset(bigbio/{bigbio_subset})`.
 
 | SciRIFF Name                                                      | Paper Link                                                                                                                                                                 | License    | Website / Download Link                                                                    | BigBio Subset      |
 | :---------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :--------- | :----------------------------------------------------------------------------------------- | :----------------- |

card.md

@@ -9,6 +9,8 @@ import datasets
 ds = datasets.load_dataset("allenai/SciRIFF", "4096")
 ```
 
+Code to create the dataset, train models on SciRIFF, and perform evaluation is available at our GitHub repo: https://github.com/allenai/SciRIFF.
+
 ## Dataset details
 
 Each instance in SciRIFF has the following fields:
@@ -16,7 +18,7 @@ Each instance in SciRIFF has the following fields:
 - `input`: Task input (i.e. user message).
 - `output`: Task output (i.e. expected model response).
 - `_instance_id`: A unique id for the instance, formatted like `{task_name}:{split}:{instance_id}`. For instance, `qasa_abstractive_qa:test:182`.
-- `metadata`: Metadata on the task that this particular demonstration is an instance of. More information on the schema for task metadata can be found in the [SciRIFF GitHub repo](https://github.com/allenai/SciRIFF).
+- `metadata`: Task metadata. More information on the schema for task metadata can be found in the [SciRIFF GitHub repo](https://github.com/allenai/SciRIFF).
   - `task_family`: The category to which this task belongs. Options include `summarization`, `ie`, `qa`, `entailment`, and `classification`. Some categories have sub-categories which are largely self-explanatory; see the [repo](https://github.com/allenai/SciRIFF) for more information.
   - `domains`: Scientific field(s) that the task covers. Options include: `clinical_medicine`, `biomedicine`, `chemistry`, `artificial_intelligence`, `materials_science`, and `misc`.
   - `input_context`: Whether the input is a paragraph, full text, etc. Options include: `sentence`, `paragraph`, `multiple_paragraphs` (including full paper text), and `structured` (e.g. code for a LaTex table).
@@ -25,11 +27,11 @@ Each instance in SciRIFF has the following fields:
 
 ## License
 
-SciRIFF is licensed under `ODC-By`.
+SciRIFF is licensed under `ODC-By`. Licenses of the datasets from which SciRIFF is derived are listed [below](#task-provenance).
 
 ## Task provenance
 
-SciRIFF was created by repurposing existing scientific literature understanding datasets. Below we provide information on the source data for each SciRIFF task, including license information on individual datasets where available. Where possible, we leveraged the excellent [BigBIO](https://github.com/bigscience-workshop/biomedical) collection as a starting point, rather than reprocessing datasets from scratch. In the table below, we include the name of the BigBio subset for all tasks included in BigBio; these can be loaded like `datasets.load_dataset(bigbio/{bigbio_subset})`.
+SciRIFF was created by repurposing existing scientific literature understanding datasets. Below we provide information on the source data for each SciRIFF task, including license information on individual datasets where available. Where possible, we leveraged the [BigBIO](https://github.com/bigscience-workshop/biomedical) collection as a starting point, rather than reprocessing datasets from scratch. In the table below, we include the name of the BigBio subset for all tasks available in BigBio; these can be loaded like `datasets.load_dataset(bigbio/{bigbio_subset})`.
 
 | SciRIFF Name                                                      | Paper Link                                                                                                                                                                 | License    | Website / Download Link                                                                    | BigBio Subset      |
 | :---------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :--------- | :----------------------------------------------------------------------------------------- | :----------------- |