datasets-knowledge-embedding
Synopsis
This project collects different datasets used in various knowledge embedding related papers. It also standardizes the format of these datasets, making it easier to use them in the evaluation of new works.
The datasets can be downloaded from the release page.
For licensing information, please refer to the original dataset license file.
If you are using this collection of datasets please consider to start
Datasets format
Every subfolder in this repo is a single dataset.
Every folder contains the following 18 files.
| File name | Description |
|---|---|
edges_as_text_{train,valid,test}.tsv |
These three files contain the three splits of the dataset where entities and relations are in a textual form (i.e. italy locatedin europe). |
edges_as_text_all.tsv |
The concatenation of edges_as_text_train.tsv, edges_as_text_valid.tsv, and edges_as_text_test.tsv. |
edges_as_id_{train,valid,test}.tsv |
These three files contain the three splits of the dataset where entities and relations are mapped to a numerical ID (i.e. 38 1 2). Entities and relations that are more frequent are mapped to lower integers (e.g. the entity/relation with ID 0 is the most frequent entity/relation in the dataset). |
edges_as_id_all.tsv |
The concatenation of edges_as_id_train.tsv, edges_as_id_valid.tsv, and edges_as_id_test.tsv. |
map_entity_id_to_text.tsv |
This file contains the mapping from numerical IDs used for entities in edges_as_id_*.tsv to the textual representation used in edges_as_text_*.tsv (i.e. 38 italy, 2 europe). |
map_relation_id_to_text.tsv |
This file contains the mapping from numerical IDs used for relations in edges_as_id_*.tsv to the textual representation used in edges_as_text_*.tsv (i.e 1 locatedin). |
frequency_entities_{all,train,valid,test}.tsv |
These files contain the frequency of each entity in the various splits of the dataset. |
frequency_relations_{all,train,valid,test}.tsv |
These files contain the frequency of each relation in the various splits of the dataset. |
Add a new dataset
If you want to add a new dataset to this collection, first you need to create three files called train.tsv, valid.tsv, and test.tsv containing respectively the edges for the three splits train, validation and test.
The files must contain tab-separated triples of the form (head entity, relation, tail entity).
Once you did this, you can simply process the three files with the following bash script.
bash build.sh train.tsv valid.tsv test.tsv .The script uses the edgelist-mapper tool under the hood.
Datasets
The datasets are distributed in two formats, namely text-based and id-based (see the dataset format section for the difference).
COUNTRIES-S1
This dataset was introduced in On Approximate Reasoning Capabilities of Low-Rank Vector Spaces.
The link to the original dataset as released by the authors is unknown but a copy has been taken from here.
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 271 | 2 | 1159 | 1111 | 24 | 24 |
COUNTRIES-S2
This dataset was introduced in On Approximate Reasoning Capabilities of Low-Rank Vector Spaces.
The link to the original dataset as released by the authors is unknown but a copy has been taken from here.
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 271 | 2 | 1111 | 1063 | 24 | 24 |
COUNTRIES-S3
This dataset was introduced in On Approximate Reasoning Capabilities of Low-Rank Vector Spaces.
The link to the original dataset as released by the authors is unknown but a copy has been taken from here.
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 271 | 2 | 1033 | 985 | 24 | 24 |
FB15K
This dataset was introduced in Translating Embeddings for Modeling Multi-relational Data.
The original dataset as released by the authors is available here.
Entities in this dataset are represented trough the Freebase ids (i.e.
/m/07l450, /film/film/genre, /m/082gq). Since they are hard to read we are considering to map them to Wikipedia pages (i.e.The_Last_King_of_scotland_(film), /film/film/genre, War_film).
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 14951 | 1345 | 592213 | 483142 | 50000 | 59071 |
FB15K-237
This dataset was introduced in Observed versus latent features for knowledge base and text inference.
The original dataset as released by the authors is available here.
Entities in this dataset are represented trough the Freebase ids (i.e.
/m/07l450, /film/film/genre, /m/082gq). Since they are hard to read we are considering to map them to Wikipedia pages (i.e.The_Last_King_of_scotland_(film), /film/film/genre, War_film).
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 14541 | 237 | 310116 | 272115 | 17535 | 20466 |
KINSHIP
This dataset was introduced in Learning systems of concepts with an infinite relational model.
The original dataset as released by the authors is available here.
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 104 | 25 | 10686 | 8544 | 1068 | 1074 |
NATIONS
This dataset was introduced in Learning systems of concepts with an infinite relational model.
The original dataset as released by the authors is available here.
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 14 | 55 | 1992 | 1592 | 199 | 201 |
UMLS
This dataset was introduced in Learning systems of concepts with an infinite relational model.
The original dataset as released by the authors is available here.
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 135 | 46 | 6529 | 5216 | 652 | 661 |
WN18
This dataset was introduced in Translating Embeddings for Modeling Multi-relational Data.
The original dataset as released by the authors is available here.
In the original dataset, the entities are represented trough the WordNet offset id (i.e.
01257145 derivationally_related_form 07488875), but the version distributed here has the offsets mapped to WordNet synsets that can be read by thenltklibrary (i.e.sensual.s.02 derivationally_related_form sensuality.n.01).
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 41105 | 18 | 151442 | 141442 | 5000 | 5000 |
WN18RR
This dataset was introduced in Convolutional 2D Knowledge Graph Embeddings.
The original dataset as released by the authors is available here.
In the original dataset, the entities are represented trough the WordNet offset id (i.e.
01257145 derivationally_related_form 07488875), but the version distributed here has the offsets mapped to WordNet synsets that can be read by thenltklibrary (i.e.sensual.s.02 derivationally_related_form sensuality.n.01).
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 41105 | 11 | 93003 | 86835 | 3034 | 3134 |
YAGO3-10
This dataset was introduced in Convolutional 2D Knowledge Graph Embeddings.
The original dataset as released by the authors is available here.
| Entities | Relation Types | Edges | Train Edges | Validation Edges | Test Edges |
|---|---|---|---|---|---|
| 123182 | 37 | 1089040 | 1079040 | 5000 | 5000 |
Authors
- Simone Primarosa - simonepri
See also the list of contributors who participated in this project.
License
This project is licensed under the MIT License - see the license file for details.