sylloge 0.2.1

Small library to simplify collecting and loading of entity alignment benchmark datasets

sylloge

This simple library aims to collect entity-alignment benchmark datasets and make them easily available.

Usage

Load benchmark datasets:

>>> from sylloge import OpenEA
>>> ds = OpenEA()
>>> ds
OpenEA(backend=pandas, graph_pair=D_W, size=15K, version=V1, rel_triples_left=38265, rel_triples_right=42746, attr_triples_left=52134, attr_triples_right=138246, ent_links=15000, folds=5)
>>> ds.rel_triples_right.head()
                                       head                             relation                                    tail
0   http://www.wikidata.org/entity/Q6176218   http://www.wikidata.org/entity/P27     http://www.wikidata.org/entity/Q145
1   http://www.wikidata.org/entity/Q212675  http://www.wikidata.org/entity/P161  http://www.wikidata.org/entity/Q446064
2   http://www.wikidata.org/entity/Q13512243  http://www.wikidata.org/entity/P840      http://www.wikidata.org/entity/Q84
3   http://www.wikidata.org/entity/Q2268591   http://www.wikidata.org/entity/P31   http://www.wikidata.org/entity/Q11424
4   http://www.wikidata.org/entity/Q11300470  http://www.wikidata.org/entity/P178  http://www.wikidata.org/entity/Q170420
>>> ds.attr_triples_left.head()
                                  head                                          relation                                               tail
0  http://dbpedia.org/resource/E534644                http://dbpedia.org/ontology/imdbId                                            0044475
1  http://dbpedia.org/resource/E340590               http://dbpedia.org/ontology/runtime  6480.0^^<http://www.w3.org/2001/XMLSchema#double>
2  http://dbpedia.org/resource/E840454  http://dbpedia.org/ontology/activeYearsStartYear     1948^^<http://www.w3.org/2001/XMLSchema#gYear>
3  http://dbpedia.org/resource/E971710       http://purl.org/dc/elements/1.1/description                          English singer-songwriter
4  http://dbpedia.org/resource/E022831       http://dbpedia.org/ontology/militaryCommand                     Commandant of the Marine Corps
>>> ds.ent_links.head()
                                  left                                    right
0  http://dbpedia.org/resource/E123186    http://www.wikidata.org/entity/Q21197
1  http://dbpedia.org/resource/E228902  http://www.wikidata.org/entity/Q5909974
2  http://dbpedia.org/resource/E718575   http://www.wikidata.org/entity/Q707008
3  http://dbpedia.org/resource/E469216  http://www.wikidata.org/entity/Q1471945
4  http://dbpedia.org/resource/E649433  http://www.wikidata.org/entity/Q1198381

You can get a canonical name for a dataset instance to use e.g. to create folders to store experiment results:

   >>> ds.canonical_name
   'openea_d_w_15k_v1'

Create id-mapped dataset for embedding-based methods:

>>> from sylloge import IdMappedEADataset
>>> id_mapped_ds = IdMappedEADataset.from_ea_dataset(ds)
>>> id_mapped_ds
IdMappedEADataset(rel_triples_left=38265, rel_triples_right=42746, attr_triples_left=52134, attr_triples_right=138246, ent_links=15000, entity_mapping=30000, rel_mapping=417, attr_rel_mapping=990, attr_mapping=138836, folds=5)
>>> id_mapped_ds.rel_triples_right
[[26048   330 16880]
 [19094   293 23348]
 [16554   407 29192]
 ...
 [16480   330 15109]
 [18465   254 19956]
 [26040   290 28560]]

You can use dask as backend for larger datasets:

>>> ds = OpenEA(backend="dask")
>>> ds
OpenEA(backend=dask, graph_pair=D_W, size=15K, version=V1, rel_triples_left=38265, rel_triples_right=42746, attr_triples_left=52134, attr_triples_right=138246, ent_links=15000, folds=5)

Which replaces pandas DataFrames with dask DataFrames.

Datasets can be written/read as parquet via to_parquet or read_parquet. After the initial read datasets are cached using this format. The cache_path can be explicitly set and caching behaviour can be disable via use_cache=False, when initalizing a dataset.

Some datasets come with pre-determined splits:

tree ~/.data/sylloge/open_ea/cached/D_W_15K_V1 
├── attr_triples_left_parquet
├── attr_triples_right_parquet
├── dataset_names.txt
├── ent_links_parquet
├── folds
│   ├── 1
│   │   ├── test_parquet
│   │   ├── train_parquet
│   │   └── val_parquet
│   ├── 2
│   │   ├── test_parquet
│   │   ├── train_parquet
│   │   └── val_parquet
│   ├── 3
│   │   ├── test_parquet
│   │   ├── train_parquet
│   │   └── val_parquet
│   ├── 4
│   │   ├── test_parquet
│   │   ├── train_parquet
│   │   └── val_parquet
│   └── 5
│       ├── test_parquet
│       ├── train_parquet
│       └── val_parquet
├── rel_triples_left_parquet
└── rel_triples_right_parquet

some don't:

tree ~/.data/sylloge/oaei/cached/starwars_swg
├── attr_triples_left_parquet
│   └── part.0.parquet
├── attr_triples_right_parquet
│   └── part.0.parquet
├── dataset_names.txt
├── ent_links_parquet
│   └── part.0.parquet
├── rel_triples_left_parquet
│   └── part.0.parquet
└── rel_triples_right_parquet
    └── part.0.parquet

Installation

pip install sylloge 

Datasets

Dataset family name	Year	# of Datasets	Sources	References
OpenEA	2020	16	DBpedia, Yago, Wikidata	Paper, Repo
MovieGraphBenchmark	2022	3	IMDB, TMDB, TheTVDB	Paper, Repo
OAEI	2022	5	Fandom wikis	Paper, Website