Curation Rationale update

README.md

@@ -61,7 +61,7 @@ task_ids:
 
 ### Dataset Summary
 
-The Real-world Annotation for Few-shot Tasks (RAFT) dataset is an aggregation of English-language datasets found in the real world. Associated with each dataset is a binary or multiclass classification task, intended to improve our understanding of how language models perform on tasks that have concrete, real-world value. Only 50 labeled examples are provided in each dataset.
+The Real-world Annotated Few-shot Tasks (RAFT) dataset is an aggregation of English-language datasets found in the real world. Associated with each dataset is a binary or multiclass classification task, intended to improve our understanding of how language models perform on tasks that have concrete, real-world value. Only 50 labeled examples are provided in each dataset.
 
 ### Supported Tasks and Leaderboards
 
@@ -80,12 +80,12 @@ RAFT is entirely in American English (en-US).
 | ----------- | ----------- |
 | Ade Corpus V2 | <pre>Sentence: No regional side effects were noted.<br>ID: 0<br>Label: 2</pre> |
 | Banking 77 | <pre>Query: Is it possible for me to change my PIN number?<br>ID: 0<br>Label: 23<br></pre> |
-| Neurips Impact Statement Risks  | <pre>Paper title: Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation...<br>Paper link: https://proceedings.neurips.cc/paper/2020/file/ec1f764517b7ffb52057af6df18142b7-Paper.pdf...<br>Impact statement: This work makes the first attempt to search for all key components of panoptic pipeline and manages to accomplish this via the p...<br>ID: 0<br>Label: 1</pre> |
+| NeurIPS Impact Statement Risks  | <pre>Paper title: Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation...<br>Paper link: https://proceedings.neurips.cc/paper/2020/file/ec1f764517b7ffb52057af6df18142b7-Paper.pdf...<br>Impact statement: This work makes the first attempt to search for all key components of panoptic pipeline and manages to accomplish this via the p...<br>ID: 0<br>Label: 1</pre> |
 | One Stop English  | <pre>Article: For 85 years, it was just a grey blob on classroom maps of the solar system. But, on 15 July, Pluto was seen in high resolution ...<br>ID: 0<br>Label: 3<br></pre> |
 | Overruling  | <pre>Sentence: in light of both our holding today and previous rulings in johnson, dueser, and gronroos, we now explicitly overrule dupree....<br>ID: 0<br>Label: 2<br></pre> |
 | Semiconductor Org Types  | <pre>Paper title: 3Gb/s AC-coupled chip-to-chip communication using a low-swing pulse receiver...<br>Organization name: North Carolina State Univ.,Raleigh,NC,USA<br>ID: 0<br>Label: 3<br></pre> |
 | Systematic Review Inclusion  | <pre>Title: Prototyping and transforming facial textures for perception research...<br>Abstract: Wavelet based methods for prototyping facial textures for artificially transforming the age of facial images were described. Pro...<br>Authors: Tiddeman, B.; Burt, M.; Perrett, D.<br>Journal: IEEE Comput Graphics Appl<br>ID: 0<br>Label: 2</pre> |
-| Tai Safety Research  |  <pre>Title: Malign generalization without internal search<br>Abstract Note: In my last post, I challenged the idea that inner alignment failures should be explained by appealing to agents which perform ex...<br>Url: https://www.alignmentforum.org/posts/ynt9TD6PrYw6iT49m/malign-generalization-without-internal-search...<br>Publication Year: 2020<br>Item Type: blogPost<br>Author: Barnett, Matthew<br>Publication Title: AI Alignment Forum<br>ID: 0<br>Label: 1</pre> | 
+| TAI Safety Research  |  <pre>Title: Malign generalization without internal search<br>Abstract Note: In my last post, I challenged the idea that inner alignment failures should be explained by appealing to agents which perform ex...<br>Url: https://www.alignmentforum.org/posts/ynt9TD6PrYw6iT49m/malign-generalization-without-internal-search...<br>Publication Year: 2020<br>Item Type: blogPost<br>Author: Barnett, Matthew<br>Publication Title: AI Alignment Forum<br>ID: 0<br>Label: 1</pre> | 
 | Terms Of Service | <pre>Sentence: Crowdtangle may change these terms of service, as described above, notwithstanding any provision to the contrary in any agreemen...<br>ID: 0<br>Label: 2<br></pre> |
 | Tweet Eval Hate  | <pre>Tweet: New to Twitter-- any men on here know what the process is to get #verified?...<br>ID: 0<br>Label: 2<br></pre> |
 | Twitter Complaints  | <pre>Tweet text: @HMRCcustomers No this is my first job<br>ID: 0<br>Label: 2</pre> |
@@ -116,7 +116,7 @@ The training examples were chosen at random. No attempt was made to ensure that
 |--------------------------------|------------|-----------|---|
 | Ade Corpus V2                  | 50         | 5000      |   |
 | Banking 77                     | 50         | 5000      |   |
-| Neurips Impact Statement Risks | 50         | 150       |   |
+| NeurIPS Impact Statement Risks | 50         | 150       |   |
 | One Stop English               | 50         | 518       |   |
 | Overruling                     | 50         | 2350      |   |
 | Semiconductor Org Types        | 50         | 449       |   |
@@ -131,14 +131,26 @@ The training examples were chosen at random. No attempt was made to ensure that
 
 ### Curation Rationale
 
-[More Information Needed]
+Generally speaking, the rationale behind RAFT was to create a benchmark for evaluating NLP models that didn't consist of contrived or artificial data sources, for which the tasks weren't originally assembled for the purpose of testing NLP models. However, each individual dataset in RAFT was collected independently. For the majority of datasets, we only collected them second-hand from existing curated sources. The datasets that we curated are: 
+* NeurIPS impact statement risks
+* Semiconductor org types
+* TAI Safety Research
+
+Each of these three datasets was sourced from our existing collaborators at Ought. They had used our service, Elicit, to analyze their dataset in the past, and we contact them to include their dataset and the associated classification task in the benchmark. For all datasets, more information is provided in our paper. For the ones which we did not curate, we provide a link to the dataset. For the ones which we did, we provide a datasheet that elaborates on many of the topics here in greater detail. 
+
+For the three datasets that we introduced:
+* **NeurIPS impact statement risks** The dataset was created to evaluate the then new requirement for authors to include an "impact statement" in their 2020 NeurIPS papers. Had it been successful? What kind of things did authors mention the most? How long were impact statements on average? Etc.
+* **Semiconductor org types** The dataset was originally created to understand better which countries’ organisations have contributed most to semiconductor R\&D over the past 25 years using three main conferences. Moreover, to estimate the share of academic and private sector contributions, the organisations were classified as “university”, “research institute” or “company”.
+* **TAI Safety Research** The primary motivations for assembling this database were to: (1) Aid potential donors in assessing organizations focusing on TAI safety by collecting and analyzing their research output. (2) Assemble a comprehensive bibliographic database that can be used as a base for future projects, such as a living review of the field.
+
 
 ### Source Data
 
 #### Initial Data Collection and Normalization
 
-[More Information Needed]
-
+* **NeurIPS impact statement risks** 
+* **Semiconductor org types** 
+* **TAI Safety Research** 
 #### Who are the source language producers?
 
 [More Information Needed]
@@ -185,12 +197,12 @@ RAFT aggregates many other datasets, each of which is provided under its own lic
 | ----------- | ----------- |
 | Ade Corpus V2 | Unlicensed |
 | Banking 77 | CC BY 4.0 |
-| Neurips Impact Statement Risks  | MIT License/CC BY 4.0 |
+| NeurIPS Impact Statement Risks  | MIT License/CC BY 4.0 |
 | One Stop English  | CC BY-SA 4.0 |
 | Overruling  | Unlicensed |
 | Semiconductor Org Types  | CC BY-NC 4.0 |
 | Systematic Review Inclusion  | CC BY 4.0 |
-| Tai Safety Research  | CC BY-SA 4.0 |
+| TAI Safety Research  | CC BY-SA 4.0 |
 | Terms Of Service | Unlicensed |
 | Tweet Eval Hate  | Unlicensed |
 | Twitter Complaints  | Unlicensed |