| --- |
| license: other |
| language: |
| - en |
| task_categories: |
| - question-answering |
| - text-generation |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # ZsRE |
|
|
| Canonical ZsRE model-editing splits, repackaged as JSON Lines for direct use |
| with `datasets.load_dataset("CrowdMind/ZsRE")`. The train and test files |
| preserve the source records and fields without synthetic additions. |
|
|
| ## Splits |
|
|
| - `train.jsonl`: 163,196 records from the ROME/MEND training split. |
| - `test.jsonl`: 19,086 records from the ROME/MEND evaluation split, exposed as |
| `test` here. |
|
|
| Each row contains `subject`, `src`, `pred`, `rephrase`, `alt`, `answers`, |
| `loc`, `loc_ans`, and `cond`. In this model-editing format, `src` is the edit |
| prompt, `alt` is the requested new answer, `answers` contains the original |
| answer(s), `rephrase` tests generalization, and `loc` / `loc_ans` test locality. |
|
|
| ## Provenance and license |
|
|
| The split files are from the [ROME project data archive](https://rome.baulab.info/data/dsets/) |
| (`zsre_mend_train.json` and `zsre_mend_eval.json`). The underlying benchmark |
| is ZsRE from Levy et al., [“Zero-Shot Relation Extraction via Reading |
| Comprehension”](https://aclanthology.org/K17-1034/). The source archive makes |
| the data publicly downloadable but does not state a separate data license; |
| this repository therefore does not claim a new license for the data. Please |
| refer to the original sources for terms and attribution. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{levy-etal-2017-zero, |
| title = {Zero-Shot Relation Extraction via Reading Comprehension}, |
| author = {Levy, Omer and Seo, Minjoon and Choi, Eunsol and Zettlemoyer, Luke}, |
| booktitle = {Proceedings of the 21st Conference on Computational Natural Language Learning}, |
| year = {2017} |
| } |
| ``` |
|
|
