What problem does it solve?
Natural language processing and translation tasks are difficult to implement reliably on-device, requiring careful handling of tokenization, thread safety, model assets, and language availability to avoid crashes or incorrect results. This Skill provides clear patterns and guarded workflows for detecting language, tagging parts of speech, extracting named entities, scoring sentiment, producing embeddings, and translating text within iOS, macOS, and visionOS applications.
Core Features & Use Cases
- Tokenization & Tagging: Word, sentence, and paragraph tokenization plus part-of-speech tagging for content analysis and UI highlighting.
- Named Entity Recognition & Sentiment: Extract people, places, organizations and compute sentiment scores for moderation, summarization, or UX tailoring.
- Embeddings & Similarity: Generate word and sentence embeddings for semantic search, recommendations, and clustering.
- Translation: Present system translation UI or perform programmatic and batch translations with model availability checks for offline use.
- Use Case: Integrate into a chat app to auto-detect language, surface named entities, compute sentiment for messages, and offer inline translation or similarity matching for replies.
Quick Start
Use the natural-language skill to detect language, extract named entities, compute sentiment scores, generate embeddings for similarity, or translate short text in an iOS app.
