arXiv:2608.23263v1 Announce Type: new Abstract: The FAIR Digital Object (FDO) framework mandates that metadata attribute values be expressed as persistent identifiers (PIDs) wherever possible, to pro...
The paper introduces an end‑to‑end pipeline that harvests, validates, and models links between scholarly articles and their source code from journals such as JOSS, SoftwareX, and IPOL, as well as SIGMOD ARI reproducibility reports. It produces a curated set of 4,397 DOI‑repository pairs and defines two Wikidata‑based application profiles—one for articles and one for software—aligned with schema.org and CodeMeta. Using these profiles, the authors created 4,182 new Wikidata software items linked to their papers, while only 82 repositories were previously represented, and they demonstrate compatibility with the COAR Notify protocol for future live enrichment.
arXiv:2608. 14228v1 Announce Type: new Abstract: Life science knowledge graphs make large collections of structured data available through SPARQL, but each resource uses its own schema, identifiers, and links.
arXiv:2608. 10644v1 Announce Type: new Abstract: Extraction produces candidate entities and relationships; writing them into a graph is where identity is decided, and identity decisions are destructive in a way extraction errors are not.
arXiv:2607. 28662v1 Announce Type: new Abstract: Large language models extract entities and relationships from unstructured documents fluently but inconsistently: type vocabularies fracture across documents, the same person surfaces under several name variants, relationships duplicate, and distinct individuals who share a name risk silent conflation.
arXiv:2608.28642v1 Announce Type: new Abstract: Knowledge graphs used by agentic systems are often treated as flat stores of extracted triples, with little record of who owns a fact, why it was admit...
arXiv:2606. 05415v1 Announce Type: cross Abstract: Real-world data spans tables, documents, and semi-structured files with implicit semantics.
arXiv:2607. 05970v1 Announce Type: cross Abstract: Dataset search depends heavily on metadata, making LLM-generated metadata a consequential form of synthetic content in retrieval systems.
The paper introduces EXYGEN, a framework that enables conversational access to large knowledge graphs by combining VoID descriptions, ShEx schemas, retrieved triples, and example question‑query pairs in a retrieval‑augmented generation pipeline. On the SciQA benchmark, this approach achieves an exact‑match score of 0.419 without fine‑tuning any large language model, and shows that larger general‑purpose LLMs can outperform smaller code‑specialized ones when provided sufficient context. To scale metadata generation for very large KGs, the authors propose a predicate‑coverage‑aware parallel graph sampling strategy that preserves structural diversity, reduces runtime by over 80× on OpenCitations Meta and GESIS, and is the only tractable method for obtaining complete metadata on ORKG.
arXiv:2607. 14494v1 Announce Type: new Abstract: Complex knowledge base question answering (KBQA) is commonly approached through either information retrieval over a question-specific subgraph or semantic parsing into an executable logical form.
arXiv:2609.16498v1 Announce Type: cross Abstract: Research data repositories are essential infrastructure for scientific inquiry and for ensuring that datasets follow FAIR (Findable, Accessible, Inte...
The paper introduces GPTKB 2.0, a method for building disambiguated knowledge bases directly from large language models. It addresses the lack of native entity representation in LLMs by performing on‑the‑fly disambiguation of entities, relations, and classes, achieving a million‑scale KB with over 1 million disambiguated entities and 38.4 million triples. The authors analyze trade‑offs among accuracy, scale, and cost, and release the system at https://gptkb.org/.