Inhalt
The way we use terminology has changed. These days, termbases are essential for more than just translators and writers. They're also feeding AI models, driving intelligent search, and powering knowledge graphs. But making a termbase work for both people and machines has its ups and downs. In this session, we'll share how we started the journey to evolve our multilingual corporate termbase into an AI-ready knowledge asset - and the practical steps we're taking along the way. You'll learn how we cleaned and structured our data, applied the right metadata, and balanced linguistic quality with machine-readability. We'll also talk about the challenges we faced in practice, how we worked with the AI, content, and taxonomy teams at Philips, and the governance practices that helped us grow. You'll get practical insights, honest lessons, and solutions you can actually apply.
Das lernen Sie
Learn how we improved our termbase for AI use, defined key metadata, balanced human and machine needs, managed work at scale, and tackled real-world challenges.