wbsg-uni-mannheim/wdc-pave

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wbsg-uni-mannheim/wdc-pave

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Web Data Commons - Using LLMs for Product Attribute Value Extraction and Normalization

MatchGPT

This repository contains code and extensive prompt examples to reproduce and extend the experiments in our papers "Using ChatGPT for Entity Matching" and "Entity Matching using Large Language Models".

Jupyter Notebook

contrastive-product-matching

This repository contains the code to reproduce the experiments of the poster "Supervised Contrastive Learning for Product Matching"

productbert-intermediate

This repository contains code and data download scripts for the paper "Intermediate Training of BERT for Product Matching" by Ralph Peeters, Christian Bizer and Goran Glavaš.

ExtractGPT

Attribute Value Extraction using Large Language Models

wdc-lspc-v2

This repository contains code and data download scripts for the paper "Using schema.org annotations for training and maintaining product matchers" by Ralph Peeters, Anna Primpeli, Benedikt Wichtlhuber and Christian Bizer.

Jupyter Notebook

productCategorization

This repository contains code and data download instructions for the workshop paper "Improving Hierarchical Product Classification using Domain-specific Language Modelling" by Alexander Brinkmann and Christian Bizer.

jointbert

This repository contains the code and data download links to reproduce the experiments of the PVLDB paper "Dual-Objective Fine-Tuning of BERT for Entity Matching" by Ralph Peeters and Christian Bizer.

wdcproducts

This repository contains the code and data download links to reproduce building the WDC Products Benchmark.

TabAnnGPT

This repository contains the code for the experiments run in the papers "Column Type Annotation using ChatGPT" and "Column Property Annotation using Large Language Models".

Jupyter Notebook

WDCFramework

Java Framework which is used by the Web Data Commons project to extract Microdata, Microformats and RDFa data, Web graphs, and HTML tables from the web crawls provided by the Common Crawl Foundation.

SC-Block

SC-Block is a supervised contrastive blocking method which combines supervised contrastive learning for positioning records in an embedding space and nearest neighbour search for candidate set building.

UnsupervisedBootAL

Unsupervised Bootstrapping of Active Learning for Entity Resolution

Jupyter Notebook

EntityMatchingTaskProfiler

Code for profiling entity matching tasks using the dimensions described in the following paper: Primpeli, Anna, and Christian Bizer. "Profiling entity matching benchmark tasks." Proceedings of the 29th ACM International Conference on Information & Knowledge Management. 2020.

wdc-sotab

Jupyter Notebook

ALMSER-GB

This repository contains the code and data for reproducing the results of the paper "Graph-boosted Active Learning for Multi-Source Entity Resolution" presented at ISWC2021.

Jupyter Notebook

SubsetCreatorJupyterNBs

Jupyter notebooks used to create the schema.org subsets from the MD and JSON-LD corpus for the WDC 2020 structured data extraction.

pie_chatgpt

Product Information Extraction using ChatGPT

Jupyter Notebook

schemaorg-tables

This repository contains the code and data download links to reproduce the building process of the 2021 Schema.org Table Corpus.

ALMSER-GEN

This repository contains the code and data for reproducing the results of the paper "Active Learning for Multi-Source Entity Matching: How do the Characteristics of the Task Impact Performance?" .

wdc-page

This repository contains the source files of the Web Data Commons website and is used to maintain the site. The Web Data Commons project extracts structured data from the Common Crawl

TailorMatch

This repository contains code and comprehensive examples to replicate and build upon the experiments presented in our paper “Fine-tuning Large Language Models for Entity Matching” The repository provides resources for implementing fine-tuning techniques on large language models specifically for entity matching tasks.

Jupyter Notebook