A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.

Related tags

Text Data & NLPKGEval
Overview

KGEval

A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.

The framework and experimental results are described in Ben Rim et al. 2021 (Outstanding Paper Award, AKBC 2021).

Instructions

Create a virtual environment

virtualenv -p python3.6 eval_env
source eval_env/bin/activate
pip install -r requirements.txt

Download data

In the main folder, run:

source data/download.sh

Download model

If you want to test the framework immediately, you can download pre-trained Pykeen models by running:

source download_models.sh

Generate behavioral tests

Symmetry Tests

Can choose --dataset FB15K237, WN18RR, YAGO310

python tests/run.py --dataset FB15K237 --mode generate --capability symmetry

This should result into the following output, and the files for each test set will be added under behavioral_tests\dataset\symmetry:

2021-10-03 23:37:35,060 - [INFO] - Preparing test sets for the dataset FB15K237
2021-10-03 23:37:37,621 - [INFO] - ########################## <----TRAIN---> ############################
2021-10-03 23:37:37,621 - [INFO] - 0 repetitions removed
2021-10-03 23:37:37,621 - [INFO] - 272115 triples remaining in train set
2021-10-03 23:37:37,621 - [INFO] - 6778 symmetric triples found in train set
2021-10-03 23:37:37,786 - [INFO] - ########################## <----TEST---> ############################
2021-10-03 23:37:37,786 - [INFO] - 0 repetitions removed
2021-10-03 23:37:37,786 - [INFO] - 20466 triples remaining in test set
2021-10-03 23:37:37,786 - [INFO] - 113 symmetric triples found in test set
2021-10-03 23:37:37,806 - [INFO] - ########################## <----VALID---> ############################
2021-10-03 23:37:37,806 - [INFO] - 0 repetitions removed
2021-10-03 23:37:37,806 - [INFO] - 17535 triples remaining in valid set
2021-10-03 23:37:37,806 - [INFO] - 113 symmetric triples found in valid set
2021-10-03 23:37:39,106 - [INFO] - #################### <---TEST SET 1: MEMORIZATION ---> ##########################
2021-10-03 23:37:39,106 - [INFO] - There are 5470 entries in the memorization set (occur in both directions)
2021-10-03 23:37:39,106 - [INFO] - #################### <---TEST SET 2: ONE DIRECTION SEEN ---> ##########################
2021-10-03 23:37:39,106 - [INFO] - There are 1308 entries not shown in both directions (to be reversed for testing)
2021-10-03 23:37:39,836 - [INFO] - #################### <--- SYMMETRIC RELATIONS ---> ##########################
2021-10-03 23:37:39,836 - [INFO] - TRAIN SET contains 6778 symmetric entries
2021-10-03 23:37:39,836 - [INFO] - TEST SET contains  113 symmetric entries with 113 not in training
2021-10-03 23:37:39,836 - [INFO] - VALID SET contains 113 symmetric entries with 113 not in training
2021-10-03 23:37:39,839 - [INFO] - #################### <---TEST SET 3: UNSEEN INSTANCES ---> ##########################
2021-10-03 23:37:39,840 - [INFO] - There are 226 entries that are not seen in any direction in training
2021-10-03 23:37:40,267 - [INFO] - #################### <---TEST SET 4: ASYMMETRY ---> ##########################
2021-10-03 23:37:40,267 - [INFO] - There are 3000 asymmetric entries in test set added to test 4

Hierarchy Tests

Only available for FB15K237 dataset

python tests/run.py --dataset FB15K237 --mode generate --capability hierarchy

The output should be and will be available under behavioral_tests/dataset/hierarchy/, the naming of the files corresponds to triples where the tail belongs to a specified level. For example, 1.txt contains triples where the tail has a type of level 1 in the entity type hierarchy :

2021-10-04 01:38:13,517 - [INFO] - Results of Hierarchy Behavioral Tests for FB15K237
2021-10-04 01:38:20,367 - [INFO] - <--------------- Entity Hiararchy statistics ----------------->
2021-10-04 01:38:20,568 - [INFO] - Level 0 contains 1 types and 3415 triples
2021-10-04 01:38:20,887 - [INFO] - Level 1 contains 66 types and 2006 triples
2021-10-04 01:38:20,900 - [INFO] - Level 2 contains 136 types and 4273 triples
2021-10-04 01:38:20,913 - [INFO] - Level 3 contains 213 types and 3560 triples
2021-10-04 01:38:20,923 - [INFO] - Level 4 contains 262 types and 3369 triples

Run Tests (pykeen models)

Symmetry behavioral tests on distmult or rotate:

python tests/run.py --dataset FB15K237 --mode test --model_name rotate

The output will be printed as shown below, and will also be available in the results folder under dataset/symmetry:

2021-10-04 14:00:57,100 - [INFO] - Starting test1 with rotate model
2021-10-04 14:03:23,249 - [INFO] - On test1, MR: 1.2407678244972578, MRR: 0.9400152688974949, [email protected]: 0.9014624953269958, [email protected]: 0.988482654094696, [email protected]: 0.9965264797210693
2021-10-04 14:03:23,249 - [INFO] - Starting test2 with rotate model
2021-10-04 14:04:15,614 - [INFO] - On test2, MR: 23.446483180428135, MRR: 0.4409348919640765, [email protected]: 0.30351680517196655, [email protected]: 0.5894495248794556, [email protected]: 0.7025994062423706
2021-10-04 14:04:15,614 - [INFO] - Starting test3 with rotate model
2021-10-04 14:04:25,364 - [INFO] - On test3, MR: 1018.9469026548672, MRR: 0.04786047740344238, [email protected]: 0.008849557489156723, [email protected]: 0.06194690242409706, [email protected]: 0.12389380484819412
2021-10-04 14:04:25,365 - [INFO] - Starting test4 with rotate model
2021-10-04 14:05:38,900 - [INFO] - On test4, MR: 4901.459, MRR: 0.07606098649786266, [email protected]: 0.9496666789054871, [email protected]: 0.893666684627533, [email protected]: 0.8823333382606506

Hierarchy behavioral tests on distmult or rotate:

   python tests/run.py --dataset FB15K237 --mode test --capability hierarchy --model_name rotate

Run Tests on other models and other frameworks

(To be added)

Owner
NEC Laboratories Europe
Research software developed at NEC Laboratories Europe
NEC Laboratories Europe
运小筹公众号是致力于分享运筹优化(LP、MIP、NLP、随机规划、鲁棒优化)、凸优化、强化学习等研究领域的内容以及涉及到的算法的代码实现。

OlittleRer 运小筹公众号是致力于分享运筹优化(LP、MIP、NLP、随机规划、鲁棒优化)、凸优化、强化学习等研究领域的内容以及涉及到的算法的代码实现。编程语言和工具包括Java、Python、Matlab、CPLEX、Gurobi、SCIP 等。 关注我们: 运筹小公众号 有问题可以直接在

运小筹 151 Dec 30, 2022
Generate text line images for training deep learning OCR model (e.g. CRNN)

Generate text line images for training deep learning OCR model (e.g. CRNN)

532 Jan 06, 2023
Tracking Progress in Natural Language Processing

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Sebastian Ruder 21.2k Dec 30, 2022
SpikeX - SpaCy Pipes for Knowledge Extraction

SpikeX is a collection of pipes ready to be plugged in a spaCy pipeline. It aims to help in building knowledge extraction tools with almost-zero effort.

Erre Quadro Srl 384 Dec 12, 2022
Based on 125GB of data leaked from Twitch, you can see their monthly revenues from 2019-2021

Twitch Revenues Bu script'i kullanarak istediğiniz yayıncıların, Twitch'den sızdırılan 125 GB'lik veriye dayanarak, 2019-2021 arası aylık gelirlerini

4 Nov 11, 2021
A unified tokenization tool for Images, Chinese and English.

ICE Tokenizer Token id [0, 20000) are image tokens. Token id [20000, 20100) are common tokens, mainly punctuations. E.g., icetk[20000] == 'unk', ice

THUDM 42 Dec 27, 2022
Code release for "COTR: Correspondence Transformer for Matching Across Images"

COTR: Correspondence Transformer for Matching Across Images This repository contains the inference code for COTR. We plan to release the training code

UBC Computer Vision Group 358 Dec 24, 2022
LewusBot - Twitch ChatBot built in python with twitchio library

LewusBot Twitch ChatBot built in python with twitchio library. Uses twitch/leagu

Lewus 25 Dec 04, 2022
Spooky Skelly For Python

_____ _ _____ _ _ _ | __| ___ ___ ___ | |_ _ _ | __|| |_ ___ | || | _ _ |__ || . || . || . || '

Kur0R1uka 1 Dec 23, 2021
Implementation of TTS with combination of Tacotron2 and HiFi-GAN

Tacotron2-HiFiGAN-master Implementation of TTS with combination of Tacotron2 and HiFi-GAN for Mandarin TTS. Inference In order to inference, we need t

SunLu Z 7 Nov 11, 2022
Implementation of Multistream Transformers in Pytorch

Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi

Phil Wang 47 Jul 26, 2022
SGMC: Spectral Graph Matrix Completion

SGMC: Spectral Graph Matrix Completion Code for AAAI21 paper "Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Learning". Data Format

Chao Chen 8 Dec 12, 2022
This repository contains the code, data, and models of the paper titled "CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summarization for 1500+ Language Pairs".

CrossSum This repository contains the code, data, and models of the paper titled "CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summ

BUET CSE NLP Group 29 Nov 19, 2022
A simple implementation of N-gram language model.

About A simple implementation of N-gram language model. Requirements numpy Data preparation Corpus Training data for the N-gram model, a text file lik

4 Nov 24, 2021
Label data using HuggingFace's transformers and automatically get a prediction service

Label Studio for Hugging Face's Transformers Website • Docs • Twitter • Join Slack Community Transfer learning for NLP models by annotating your textu

Heartex 135 Dec 29, 2022
Hostapd-mac-tod-acl - Setup a hostapd AP with MAC ToD ACL

A brief explanation This script provides a quick way to setup a Time-of-day (Tod

2 Feb 03, 2022
Flaxformer: transformer architectures in JAX/Flax

Flaxformer: transformer architectures in JAX/Flax Flaxformer is a transformer library for primarily NLP and multimodal research at Google. It is used

Google 114 Dec 29, 2022
NL. The natural language programming language.

NL A Natural-Language programming language. Built using Codex. A few examples are inside the nl_projects directory. How it works Write any code in pur

2 Jan 17, 2022
Data manipulation and transformation for audio signal processing, powered by PyTorch

torchaudio: an audio library for PyTorch The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the

1.9k Jan 08, 2023
This is a GUI program that will generate a word search puzzle image

Word Search Puzzle Generator Table of Contents About The Project Built With Getting Started Prerequisites Installation Usage Roadmap Contributing Cont

11 Feb 22, 2022