NaturalLanguage + Translation

Analyze natural language text for tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, language identification, and embeddings using NaturalLanguage. Translate text with Translation. Targets Swift 6.4 / iOS 26+.

Contents

• Framework Scope and Boundaries
• Core Capabilities Matrix
• Thread Safety and Performance
• Translation Availability
• Route by Task
• Common Mistakes
• Review Checklist
• References

Framework Scope and Boundaries

• NaturalLanguage: On-device text analysis (NLTokenizer, NLTagger, NLLanguageRecognizer, NLEmbedding, NLModel). Requires no special entitlements.
• Translation: In-app UI and programmatic language translation (TranslationSession, LanguageAvailability).
• Boundaries: Route OCR and image text recognition to vision-framework; route audio speech-to-text to speech-recognition; route generative LLM features to apple-on-device-ai; route static localization to ios-localization.

Core Capabilities Matrix

Thread Safety and Performance

[!IMPORTANT] NLTokenizer and NLTagger are not thread-safe. Do not share instances across concurrent tasks or queues. Create instances on demand or isolate them within a serial actor. NLEmbedding instances are read-only and thread-safe once loaded into memory.

Translation Availability

• .translationPresentation(isPresented:text:): iOS 17.4+, macOS 14.4+, visionOS 1.1+
• TranslationSession, .translationTask(), and LanguageAvailability: iOS 18.0+, macOS 15.0+, visionOS 2.0+
• Offline programmatic translation via TranslationSession(installedSource:target:) requires the target language packs to be already installed on device.

Route by Task

• For word/sentence tokenization, language recognition, and emoji/numeric detection, read Tokenization and Language ID.
• For POS tagging, entity extraction, sentiment analysis, and embeddings, read Tagging and Embeddings.
• For custom Core ML text classifiers and taggers with NLModel, read Custom NLModel Classifiers.
• For SwiftUI translation sheets, batch translation, and language pack availability, read Translation Patterns.

Common Mistakes

• Sharing an NLTokenizer or NLTagger across concurrent threads or Tasks without isolation.
• Passing empty strings to NLEmbedding or checking similarity without unwrapping optionals.
• Using TranslationSession offline when language packs are not installed on device.
• Performing synchronous NLP tagging or sentence embedding on the main thread during UI scrolling.
• Misinterpreting sentiment scores: scores range from -1.0 to 1.0 (0.0 is neutral, nil indicates untagged).

Review Checklist

• NLTokenizer and NLTagger used from a single thread or isolated in an actor
• Availability guards applied for TranslationSession (iOS 18+) vs presentation sheet (iOS 17.4+)
• Language availability verified with LanguageAvailability.status() before programmatic translation
• Long text analysis dispatched off @MainActor to background tasks
• NLEmbedding.wordEmbedding(for:) checked for nil availability in the target language
• Tag options include .omitWhitespace and .omitPunctuation where appropriate

References

• NaturalLanguage text analysis patterns
• Translation framework patterns and SwiftUI views
• NaturalLanguage documentation
• Translation documentation
• NLTokenizer
• NLTagger
• NLEmbedding