| --- |
| annotations_creators: |
| - no-annotation |
| language_creators: |
| - found |
| language: |
| - en |
| - de |
| license: |
| - mit |
| multilinguality: |
| - 2 languages |
| size_categories: |
| - 100K<n<1M |
| source_datasets: |
| - original |
| task_categories: |
| - syntactic-evaluation |
| task_ids: |
| - syntactic-transformations |
| --- |
| |
| # Dataset Card for syntactic_transformations |
| |
| ## Table of Contents |
| - [Dataset Description](#dataset-description) |
| - [Dataset Summary](#dataset-summary) |
| - [Supported Tasks](#supported-tasks-and-leaderboards) |
| - [Languages](#languages) |
| - [Dataset Structure](#dataset-structure) |
| - [Data Instances](#data-instances) |
| - [Data Fields](#data-instances) |
| - [Data Splits](#data-instances) |
| - [Dataset Creation](#dataset-creation) |
| - [Curation Rationale](#curation-rationale) |
| - [Source Data](#source-data) |
| - [Annotations](#annotations) |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| - [Considerations for Using the Data](#considerations-for-using-the-data) |
| - [Social Impact of Dataset](#social-impact-of-dataset) |
| - [Discussion of Biases](#discussion-of-biases) |
| - [Other Known Limitations](#other-known-limitations) |
| - [Additional Information](#additional-information) |
| - [Dataset Curators](#dataset-curators) |
| - [Licensing Information](#licensing-information) |
| - [Citation Information](#citation-information) |
| |
| ## Dataset Description |
| |
| - **Homepage:** [Needs More Information] |
| - **Repository:** https://github.com/sebschu/multilingual-transformations |
| - **Paper:** [Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models](https://aclanthology.org/2022.findings-acl.106/) |
| - **Leaderboard:** [Needs More Information] |
| - **Point of Contact:** [Aaron Mueller](mailto:amueller@jhu.edu) |
| |
| ### Dataset Summary |
| |
| This contains the the syntactic transformations datasets used in [Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models](https://aclanthology.org/2022.findings-acl.106/). It consists of English and German question formation and passivization transformations. This dataset also contains zero-shot cross-lingual transfer training and evaluation data. |
| |
| ### Supported Tasks and Leaderboards |
| |
| [Needs More Information] |
| |
| ### Languages |
| |
| English and German. |
| |
| ## Dataset Structure |
| |
| ### Data Instances |
| |
| A typical data point consists of a source sequence ("src"), a target sequence ("tgt"), and a task prefix ("prefix"). The prefix indicates whether a given sequence should be kept the same in the target (indicated by the "decl:" prefix) or transformed into a question/passive ("quest:"/"passiv:", respectively). An example follows: |
| |
| {"src": "the yak has entertained the walruses that have amused the newt.", |
| "tgt": "has the yak entertained the walruses that have amused the newt?", |
| "prefix": "quest: " |
| } |
| |
| ### Data Fields |
| |
| - src: the original source sequence. |
| - tgt: the transformed target sequence. |
| - prefix: indicates which transformation to perform to map from the source to target sequences. |
| |
| ### Data Splits |
| |
| The datasets are split into training, dev, test, and gen ("generalization") sets. The training sets are for fine-tuning the model. The dev and test sets are for evaluating model abilities on in-domain transformations. The generalization sets are for evaluating the inductive biases of the model. |
| |
| NOTE: for the zero-shot cross-lingual transfer datasets, the generalization sets are split into in-domain and out-of-domain syntactic structures. For in-domain transformations, use "gen_rc_o" for question formation or "gen_pp_o" for passivization. For out-of-domain transformations, use "gen_rc_s" for question formation or "gen_pp_s" for passivization. |
| |
| ## Dataset Creation |
| |
| ### Curation Rationale |
| |
| [Needs More Information] |
| |
| ### Source Data |
| |
| #### Initial Data Collection and Normalization |
| |
| [Needs More Information] |
| |
| #### Who are the source language producers? |
| |
| [Needs More Information] |
| |
| ### Annotations |
| |
| #### Annotation process |
| |
| [Needs More Information] |
| |
| #### Who are the annotators? |
| |
| [Needs More Information] |
| |
| ### Personal and Sensitive Information |
| |
| [Needs More Information] |
| |
| ## Considerations for Using the Data |
| |
| ### Social Impact of Dataset |
| |
| [Needs More Information] |
| |
| ### Discussion of Biases |
| |
| [Needs More Information] |
| |
| ### Other Known Limitations |
| |
| [Needs More Information] |
| |
| ## Additional Information |
| |
| ### Dataset Curators |
| |
| [Needs More Information] |
| |
| ### Licensing Information |
| |
| [Needs More Information] |
| |
| ### Citation Information |
| |
| [Needs More Information] |
