most citedKastor: Fine-tuned Small Language Models for Shape-based Active Relation Extraction

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DB2026

Preserving contextual information in cultural heritage metadata through multidimensional knowledge graphs

Lyndon Nixon, Valentina Presutti, Celian Ringwald +1

Using Knowledge Graphs (KGs) to describe Cultural Heritage Objects (CHOs) supports semantic richness and interoperability. However, standard KGs fail to capture the context-depende…

cs.DB2026

X-DigCheck: Co-Evolving Application Profiles and Knowledge Graphs, Demonstrated on the RTI Documentation of Rupe Magna

Celian Ringwald, Huseyin Erdogan, Valentina Presutti +1

We demonstrate X-DigCheck, a domain-independent environment for building and maintaining application profiles as they co-evolve with the data they describe. Profiles developed agai…

cs.CL2025

A systematic review of relation extraction task since the emergence of Transformers

Ringwald Celian, Gandon, Fabien +3

This article presents a systematic review of relation extraction (RE) research since the advent of Transformer-based models. Using an automated framework to collect and annotate pu…

cs.CL2025★ 1 cited

Overcoming the Generalization Limits of SLM Finetuning for Shape-Based Extraction of Datatype and Object Properties

Célian Ringwald, Fabien Gandon, Catherine Faron +2

Small language models (SLMs) have shown promises for relation extraction (RE) when extracting RDF triples guided by SHACL shapes focused on common datatype properties. This paper i…

cs.CL2025★ 2 cited

Kastor: Fine-tuned Small Language Models for Shape-based Active Relation Extraction

Ringwald Celian, Gandon Fabien, Faron Catherine +2

RDF pattern-based extraction is a compelling approach for fine-tuning small language models (SLMs) by focusing a relation extraction task on a specified SHACL shape. This technique…

cs.AI2025

Semantic Web and Creative AI -- A Technical Report from ISWS 2023

Raia Abu Ahmad, Reham Alharbi, Roberto Barile +74

The International Semantic Web Research School (ISWS) is a week-long intensive program designed to immerse participants in the field. This document reports a collaborative effort p…