HistoriQA-ThirdRepublic: Multi-Hop Question Answering Corpus for Historical Research, Parliamentary Debates from the French Third Republic (1870-1940)

We present HistoriQA-ThirdRepublic: a French-language dataset of multi-hop historical questions derived from parliamentary debates and newspapers of the French Third Republic. Designed in collaboration with a historian, the corpus captures complex reasoning patterns typical of historical inquiry, including cross-source synthesis, temporal reasoning, and the integration of sparse evidence. The dataset is made of 1782 questions and emphasizes multi-hop connections across heterogeneous historical documents, providing a resource for evaluating retrieval-augmented and large language model systems in domain-specific contexts. We describe the methodology for constructing the corpus, including the selection and alignment of sources, question validation, and metadata integration. While the dataset focuses on French historical documents, our methodology can be readily adapted to other languages and national corpora. Finally, we demonstrate how the corpus can support realistic evaluation scenarios for multi-hop question answering, bridging the gap between NLP benchmarks and the needs of historical scholarship.

Towards a Domain Ontology for the Analysis of Ancient Fabrics The SILKNOW Project and the Case of European Silk Heritage

In this article, we present the SILKNOW project (Silk heritage in the Knowledge Society: from punched card to Big Data, Deep Learning and visual/tangible simulations) (2018-2021). This project aimed to use Semantic Web technologies to give greater visibility to silk objects produced and consumed in Europe between the 15th and 19th centuries. Silk is a particularly important material in European history, and it has produced some exceptional objects of great historical interest. However, it is a threatened heritage that is little known to the general public. We show the interest of using Semantic Web technologies to give more visibility to such a heritage, by describing the results we have obtained. We present the methodology used to develop a knowledge graph, and in particular the different steps that were necessary to create the underlying data model, based on the CIDOC CRM or CIDOC Conceptual Reference Model. We also propose a CIDOC CRM-compatible extension to express the complex semantics of the creation and production process of ancient silk fabrics.