| --- |
| language: |
| - en |
| license: |
| - other |
| multilinguality: |
| - monolingual |
| size_categories: |
| - 1<n<1K |
| pretty_name: Relation Mapping |
| --- |
| # Dataset Card for "relbert/relation_mapping" |
| ## Dataset Description |
| - **Repository:** [RelBERT](https://github.com/asahi417/relbert) |
| - **Paper:** [https://www.jair.org/index.php/jair/article/view/10583](https://www.jair.org/index.php/jair/article/view/10583) |
| - **Dataset:** Relation Mapping |
| |
| ### Dataset Summary |
| Relation Mapping is a task to choose optimal combination of word pairs (see more detail in the [paper](https://www.jair.org/index.php/jair/article/view/10583)). |
| |
| |
| Relation mapping `M` is the set of bijective map in between two sets of terms (`A` and `B`): |
| ``` |
| [set `A`]: ("solar system", "sun", "planet", "mass", "attracts", "revolves", "gravity") |
| [set `B`]: ("atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism") |
| |
| [Relation Mapping `M`] |
| * "solar system" -> "atom" |
| * "sun" -> "nucleus" |
| * "planet" -> "electron" |
| * "mass" -> "charge" |
| * "attracts" -> "attracts" |
| * "revolves" -> "revolves" |
| * "gravity" -> "electromagnetism" |
| ``` |
| |
| ***[Relation Mapping Problem](https://www.jair.org/index.php/jair/article/view/10583)*** is the task to identify the mapping `M` given the sets of terms `A` and `B`. |
| |
| |
| ## Dataset Structure |
| ### Data Instances |
| An example looks as follows. |
| ``` |
| { |
| "id": "m10", |
| "reference": ["seeing", "understanding"], |
| "source": ["seeing", "light", "illuminating", "darkness", "view", "hidden"], |
| "target": ["understanding", "knowledge", "explaining", "confusion", "interpretation", "secret"], |
| "agreement": [68.2, 77.3, 86.4, 86.4, 68.2, 86.4], |
| "pos": ["vbg", "nn", "vbg", "nn", "nn", "jj"], |
| "target_random": ["knowledge", "interpretation", "explaining", "confusion", "understanding", "secret"] |
| } |
| ``` |
| |
| - `source`: A list of terms, which is the source of the relation mapping from. |
| - `target_random`: A list of terms, where we want to find a mapping from `source` to. |
| - `target`: A correctly ordered `target_random` that aligns with the `source`. |
| |
| Given `source` and `target_random`, the task is to predict the correct order of `target_random` so that it matches `target`. |
| In average 7 terms are in the set, so the total number of possible order is 5040. |
| |
| |
| ### Data Splits |
| | name |test| |
| |---------|----:| |
| |relation_mapping| 20 | |
| |
| |
| ### Citation Information |
| ``` |
| @article{turney2008latent, |
| title={The latent relation mapping engine: Algorithm and experiments}, |
| author={Turney, Peter D}, |
| journal={Journal of Artificial Intelligence Research}, |
| volume={33}, |
| pages={615--655}, |
| year={2008} |
| } |
| ``` |
