Papers Table annotation
“Table annotation” 태그가 달린 논문 31편 · 필터 해제
Column Property Annotation using Large Language Models
Column property annotation (CPA), also known as column relationship prediction, is the task of predicting the semantic relationship between two columns in a table given a set of candidate relationships. CPA annotations a…
Columns Property AnnotationColumn Type AnnotationData IntegrationIn-Context Learning+1Evaluating LLMs on Entity Disambiguation in Tables
Tables are crucial containers of information, but understanding their meaning may be challenging. Over the years, there has been a surge in interest in data-driven approaches based on deep learning that have increasingly…
DecoderEntity DisambiguationTable annotationStatements: Universal Information Extraction from Tables with Large Language Models for ESG KPIs
Environment, Social, and Governance (ESG) KPIs assess an organization's performance on issues such as climate change, greenhouse gas emissions, water consumption, waste management, human rights, diversity, and policies. …
Information ExtractionNamed Entity RecognitionOpen Information ExtractionRelationship Extraction (Distant Supervised)+1Synthesizing Realistic Data for Table Recognition
To overcome the limitations and challenges of current automatic table data annotation methods and random table data synthesis approaches, we propose a novel method for synthesizing annotation data specifically designed f…
Table annotationTable RecognitionTorchicTab: Semantic Table Annotation with Wikidata and Language Models
An abundance of tabular data exists and is used by a wide range of applications. However, a big portion of these data lack the semantic information necessary for users and machines to properly understand them. This lack …
Columns Property AnnotationColumn Type AnnotationGraph MatchingTable annotationArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models
Existing deep-learning approaches to semantic column type annotation (CTA) have important shortcomings: they rely on semantic types which are fixed at training time; require a large number of training samples per type an…
Column Type AnnotationTable annotationzero-shot-classificationZero-Shot LearningColumn Type Annotation using ChatGPT
Column type annotation is the task of annotating the columns of a relational table with the semantic type of the values contained in each column. Column type annotation is an important pre-processing step for data search…
Column Type AnnotationData IntegrationTable annotationA large-scale dataset for end-to-end table recognition in the wild
Table recognition (TR) is one of the research hotspots in pattern recognition, which aims to extract information from tables in an image. Common table recognition tasks include table detection (TD), table structure recog…
Table annotationTable DetectionTable RecognitionBiodivTab: Semantic Table Annotation Benchmark Construction, Analysis, and New Additions
Systems that annotate tabular data semantically have witnessed increasing attention from the community in recent years; this process is commonly known as Semantic Table Annotation (STA). Its objective is to map individua…
Table annotationSOTAB: The WDC Schema.org Table Annotation Benchmark
Understanding the semantics of table elements is a prerequisite for many data integration and data discovery tasks. Table annotation is the task of labeling table elements with terms from a given vocabulary. This paper p…
Columns Property AnnotationColumn Type AnnotationData IntegrationMissing Values+1Results of SemTab 2021
SemTab 2021 was the third edition of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, successfully collocated with the 20th International Semantic Web Conference (ISWC) and the 16th Ontology Matchi…
Graph MatchingOntology MatchingTable annotationDAGOBAH: Table and Graph Contexts for Efficient Semantic Annotation of Tabular Data
In this paper, we present the latest improvements of the DAGOBAH system that performs automatic pre-processing and semantic interpretation of tables. In particular, we report promising results obtained in the SemTab 2021…
Cell Entity AnnotationColumn Type AnnotationTable annotationKepler-aSI at SemTab 2021
In this paper, we present our system Kepler-aSI, for the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2021). This system is participating for the second time in this campaign, bringing impro…
Cell Entity AnnotationColumn Type AnnotationGraph MatchingKnowledge Graphs+1MAGIC: Mining an Augmented Graph using INK, starting from a CSV
A large portion of structured data does not yet reap the benefits of the Semantic Web. Therefore, The “Tabular Data to Knowledge Graph Matching” competition at ISWC tries to bridge this gap by evaluating and promoting th…
Cell Entity AnnotationColumn Type AnnotationGraph MatchingTable annotationJenTab Meets SemTab 2021's New Challenges
While tables are a rich source of structured information, their automated use is oftentimes prevented by the inherent ambiguity contained within. Issues ranging from mere typos over inconsistent naming conventions to hom…
Cell Entity AnnotationColumn Type AnnotationGraph MatchingTable annotationGitTables: A Large-Scale Corpus of Relational Tables
The success of deep learning has sparked interest in improving relational table tasks, like data preparation and search, with table representation models trained on large table corpora. Existing table corpora primarily c…
Information RetrievalTable annotationTABBIE: Pretrained Representations of Tabular Data
Existing work on tabular representation learning jointly models tables and associated text using self-supervised objective functions derived from pretrained language models such as BERT. While this joint pretraining impr…
Cell DetectionColumn Type AnnotationRepresentation LearningTable annotationAnnotating Columns with Pre-trained Language Models
Inferring meta information about tables, such as column headers or relationships between columns, is an active research topic in data management as we find many tables are missing some of this information. In this paper,…
Columns Property AnnotationColumn Type AnnotationManagementMulti-Task Learning+3Joint Learning of Representations for Web-tables, Entities and Types using Graph Convolutional Network
Existing approaches for table annotation with entities and types either capture the structure of table using graphical models, or learn embeddings of table entries without accounting for the complete syntactic structure.…
Table annotationbbw: Matching CSV to Wikidata via Meta-lookup
We present our publicly available semantic annotator bbw (boosted by wiki) tested at the second Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab2020). It annotates a raw CSV-table using the enti…
Entity TypingGraph MatchingNamed Entity Recognition (NER)Relation Extraction+1