#ontology

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5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.7 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.3 Study traces LLM hallucinations to competing latent associations — 1 src1.3 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.3 Study Analyzes Self-Reported Limitations in NLP Research — 1 src5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.7 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.3 Study traces LLM hallucinations to competing latent associations — 1 src1.3 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.3 Study Analyzes Self-Reported Limitations in NLP Research — 1 src

2 curated events

papersTODAY 04:00 UTC

Self-Demonstrations Improve LLM Schema-Ontology Mapping, arXiv Paper Finds

A new arXiv preprint examines how self-demonstrations, where a model generates its own worked examples before answering, affect the task of mapping relational database schemas onto a shared ontology. The authors frame the problem around semantic heterogeneity, obscure table and column names, missing metadata, and the abstraction gap that complicates enterprise knowledge integration. Results reported in the abstract suggest the self-demonstration approach is unexpectedly effective for this mapping task.

llm/ontology/knowledge-graphs/prompting

papersTODAY 04:00 UTC

EvoOntology Proposes Self-Evolving Ontology Layer for Data Agents

A new arXiv paper introduces EvoOntology, a layer designed to help data agents work across heterogeneous sources such as tables, files, and databases. The authors frame the problem as an "agent-data gap," where relevant data sits outside the agent while the agent can only reach limited context. The proposed ontology layer is meant to evolve alongside the data so agents can better interpret and query it.

agents/ontology/research/data-agents