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Table annotation

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하위 태스크: 6
평가표: 0
보존된 평가 기록: 0

Table annotation is the task of annotating a table with terms/concepts from knowledge graph or database schema. Table annotation is typically broken down into the following five subtasks:

Cell Entity Annotation (CEA)
Column Type Annotation (CTA)
Column Property Annotation (CPA)
Table Type Detection
Row Annotation

The SemTab challenge is closely related to the Table Annotation problem. It is a yearly challenge which focuses on the first three tasks of table annotation and its purpose is to benchmark different table annotation systems.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/SFIG611/tabbie

공식 코드

TABBIE: Pretrained Representations of Tabular Data

https://github.com/Wyb0627/KBLink

공식 코드

KGLink: A column type annotation method that combines knowledge graph and pre-trained language model

https://github.com/alan-turing-institute/SemAIDA

공식 코드

ColNet: Embedding the Semantics of Web Tables for Column Type Prediction

https://github.com/ds4sd/semtabnet

공식 코드

Statements: Universal Information Extraction from Tables with Large Language Models for ESG KPIs

https://github.com/iWudao/Synthesizing-Realistic-Data-for-Table-Recognition

공식 코드

Synthesizing Realistic Data for Table Recognition

https://github.com/madelonhulsebos/gittables

공식 코드

GitTables: A Large-Scale Corpus of Relational Tables

https://github.com/maxkinny/tabrecset

공식 코드

A large-scale dataset for end-to-end table recognition in the wild

https://github.com/megagonlabs/doduo

공식 코드

Annotating Columns with Pre-trained Language Models

https://github.com/megagonlabs/sato

공식 코드

Sato: Contextual Semantic Type Detection in Tables

https://github.com/mitmedialab/sherlock-project

공식 코드

Sherlock: A Deep Learning Approach to Semantic Data Type Detection

https://github.com/mkyl/chorus

공식 코드

CHORUS: Foundation Models for Unified Data Discovery and Exploration

https://github.com/penfever/archetype

공식 코드

ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models

https://github.com/phucty/MTab

공식 코드

MTab: Matching Tabular Data to Knowledge Graph using Probability Models

https://github.com/phucty/mtab_tool

공식 코드

MTab: Matching Tabular Data to Knowledge Graph using Probability Models

https://github.com/sunlab-osu/TURL

공식 코드

TURL: Table Understanding through Representation Learning

https://github.com/wbsg-uni-mannheim/tabanngpt

공식 코드

Column Type Annotation using ChatGPT

https://github.com/whnhch/accio

공식 코드

ACCIO: Table Understanding Enhanced via Contrastive Learning with Aggregations

https://github.com/2023-MindSpore-1/ms-code-217/tree/main/TCN

TCN: Table Convolutional Network for Web Table Interpretation

https://github.com/IBCNServices/Magic

https://github.com/T2KFramework/T2K

https://github.com/awslabs/hypergraph-tabular-lm

TABBIE: Pretrained Representations of Tabular Data

https://github.com/fusion-jena/jentab

https://github.com/jiofidelus/tsotsa

https://github.com/pidahbus/DCoM

Sherlock: A Deep Learning Approach to Semantic Data Type Detection

https://github.com/tsegall/fta

GitTables: A Large-Scale Corpus of Relational Tables

https://github.com/wbsg-uni-mannheim/wdc-sotab

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