Wikidated : An Evolving Knowledge Graph Dataset of Wikidata’s Revision History

Overview

Wikidated

Wikidated 1.0 is a dataset of Wikidata’s full revision history, which encodes changes between Wikidata revisions as sets of deletions and additions of RDF triples.

This repository contains the code used to generate it as well as a Python API to process it.

We are currently in the process of refactoring the code and preparing the dataset for initial public release. It will be available here soon.

Publication

We describe the Wikidated dataset and our methodology for generating it in our publication: Schmelzeisen, Dima, Staab (2021). Wikidated 1.0: An Evolving Knowledge Graph Dataset of Wikidata’s Revision History. [email protected]. If you find this dataset useful or use it in any academic work, please cite it as:

@inproceedings{conf/semweb/SchmelzeisenDS21,
  author    = {Lukas Schmelzeisen and
               Corina Dima and
               Steffen Staab},
  title     = {{Wikidated 1.0: An Evolving Knowledge Graph Dataset of Wikidata’s Revision History}},
  booktitle = {[email protected]},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {2982},
  publisher = {CEUR-WS.org},
  year      = {2021}
}

License

Copyright 2021 Lukas Schmelzeisen. Licensed under the Apache License, Version 2.0.

Owner
Lukas Schmelzeisen
PhD student at @analyticcomp (Uni Stuttgart, Germany). Interested in ML, NLP and Knowledge Graphs. Open to internships in research and industry internationally.
Lukas Schmelzeisen
USAD - UnSupervised Anomaly Detection on multivariate time series

USAD - UnSupervised Anomaly Detection on multivariate time series Scripts and utility programs for implementing the USAD architecture. Implementation

116 Jan 04, 2023
[ICLR 2022] DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR

DAB-DETR This is the official pytorch implementation of our ICLR 2022 paper DAB-DETR. Authors: Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi

336 Dec 25, 2022
Python package for Bayesian Machine Learning with scikit-learn API

Python package for Bayesian Machine Learning with scikit-learn API Installing & Upgrading package pip install https://github.com/AmazaspShumik/sklearn

Amazasp Shaumyan 482 Jan 04, 2023
The King is Naked: on the Notion of Robustness for Natural Language Processing

the-king-is-naked: on the notion of robustness for natural language processing AAAI2022 DISCLAIMER:This repo will be updated soon with instructions on

Iperboreo_ 1 Nov 24, 2022
Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019)

Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019) Introduction Official implementation of Dynamic Multi-scale Filters for Semant

23 Oct 21, 2022
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"

SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks

60 Dec 22, 2022
这是一个利用facenet和retinaface实现人脸识别的库,可以进行在线的人脸识别。

Facenet+Retinaface:人脸识别模型在Pytorch当中的实现 目录 注意事项 Attention 所需环境 Environment 文件下载 Download 预测步骤 How2predict 参考资料 Reference 注意事项 该库中包含了两个网络,分别是retinaface和

Bubbliiiing 102 Dec 30, 2022
PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric (ICCV 2021)

PrimitiveNet Source code for the paper: Jingwei Huang, Yanfeng Zhang, Mingwei Sun. [PrimitiveNet: Primitive Instance Segmentation with Local Primitive

Jingwei Huang 47 Dec 06, 2022
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s

Yi-Hsuan Tsai 782 Dec 30, 2022
(SIGIR2020) “Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback’’

Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback About This repository accompanies the real-world experiments conducted i

yuta-saito 19 Dec 01, 2022
💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena

💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena.

Heidelberg-NLP 17 Nov 07, 2022
AntiFuzz: Impeding Fuzzing Audits of Binary Executables

AntiFuzz: Impeding Fuzzing Audits of Binary Executables Get the paper here: https://www.usenix.org/system/files/sec19-guler.pdf Usage: The python scri

Chair for Sys­tems Se­cu­ri­ty 88 Dec 21, 2022
Source Code of NeurIPS21 paper: Recognizing Vector Graphics without Rasterization

YOLaT-VectorGraphicsRecognition This repository is the official PyTorch implementation of our NeurIPS-2021 paper: Recognizing Vector Graphics without

Microsoft 49 Dec 20, 2022
(IEEE TIP 2021) Regularized Densely-connected Pyramid Network for Salient Instance Segmentation

RDPNet IEEE TIP 2021: Regularized Densely-connected Pyramid Network for Salient Instance Segmentation PyTorch training and testing code are available.

Yu-Huan Wu 41 Oct 21, 2022
Open & Efficient for Framework for Aspect-based Sentiment Analysis

PyABSA - Open & Efficient for Framework for Aspect-based Sentiment Analysis Fast & Low Memory requirement & Enhanced implementation of Local Context F

YangHeng 567 Jan 07, 2023
PyTorch implementation(s) of various ResNet models from Twitch streams.

pytorch-resnet-twitch PyTorch implementation(s) of various ResNet models from Twitch streams. Status: ResNet50 currently not working. Will update in n

Daniel Bourke 3 Jan 11, 2022
Image based Human Fall Detection

Here I integrated the YOLOv5 object detection algorithm with my own created dataset which consists of human activity images to achieve low cost, high accuracy, and real-time computing requirements

UTTEJ KUMAR 12 Dec 11, 2022
Contrastive Learning for Many-to-many Multilingual Neural Machine Translation(mCOLT/mRASP2), ACL2021

Contrastive Learning for Many-to-many Multilingual Neural Machine Translation(mCOLT/mRASP2), ACL2021 The code for training mCOLT/mRASP2, a multilingua

104 Jan 01, 2023
Robust Consistent Video Depth Estimation

[CVPR 2021] Robust Consistent Video Depth Estimation This repository contains Python and C++ implementation of Robust Consistent Video Depth, as descr

Facebook Research 213 Dec 17, 2022
Sequence-to-Sequence learning using PyTorch

Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train

Elad Hoffer 514 Nov 17, 2022