Natural Language

NaturalLanguage + Translation

Analyze natural language text for tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, language identification, and word/sentence embeddings. Translate text between languages with the Translation framework.

This skill covers two related frameworks: NaturalLanguage (NLTokenizer, NLTagger, NLEmbedding) for on-device text analysis, and Translation (TranslationSession, LanguageAvailability) for language translation.

Scope boundary: Use this skill after you already have text. It owns tokenization, language identification, POS/NER tagging, sentiment, embeddings, custom NLModel classifiers/taggers, and in-app translation. Hand off OCR to vision-framework, speech-to-text to speech-recognition, UI strings and locale formatting to ios-localization, and generative summarization or Apple Intelligence workflows to apple-on-device-ai.

Contents

• Setup
• Tokenization
• Language Identification
• Part-of-Speech Tagging
• Named Entity Recognition
• Sentiment Analysis
• Text Embeddings
• Translation
• Common Mistakes
• Review Checklist
• References

Setup

Import NaturalLanguage for text analysis and Translation for language translation. No special entitlements or capabilities are required for NaturalLanguage. Translation has split availability: system translation presentation is iOS 17.4+ / macOS 14.4+, while TranslationSession, .translationTask(), LanguageAvailability, and batch translation require iOS 18+ / macOS 15+. Direct TranslationSession(installedSource:target:) is the non-UI option, but only when the source and target languages are already installed on device.

import NaturalLanguage
import Translation

NaturalLanguage classes (NLTokenizer, NLTagger) are not thread-safe. Use each instance from one thread or dispatch queue at a time.

Tokenization

Segment text into words, sentences, or paragraphs with NLTokenizer.

import NaturalLanguage

func tokenizeWords(in text: String) -> [String] {
    let tokenizer = NLTokenizer(unit: .word)
    tokenizer.string = text

    let range = text.startIndex..<text.endIndex
    return tokenizer.tokens(for: range).map { String(text[$0]) }
}

Token Units

Enumerating with Attributes

Use enumerateTokens(in:using:) to detect numeric or emoji tokens.

let tokenizer = NLTokenizer(unit: .word)
tokenizer.string = text

tokenizer.enumerateTokens(in: text.startIndex..<text.endIndex) { range, attributes in
    if attributes.contains(.numeric) {
        print("Number: \(text[range])")
    }
    return true // continue enumeration
}

Language Identification

Detect the dominant language of a string with NLLanguageRecognizer.

func detectLanguage(for text: String) -> NLLanguage? {
    NLLanguageRecognizer.dominantLanguage(for: text)
}

// Multiple hypotheses with confidence scores
func languageHypotheses(for text: String, max: Int = 5) -> [NLLanguage: Double] {
    let recognizer = NLLanguageRecognizer()
    recognizer.processString(text)
    return recognizer.languageHypotheses(withMaximum: max)
}

Constrain the recognizer to expected languages for better accuracy on short text.

let recognizer = NLLanguageRecognizer()
recognizer.languageConstraints = [.english, .french, .spanish]
recognizer.processString(text)
let detected = recognizer.dominantLanguage

Part-of-Speech Tagging

Identify nouns, verbs, adjectives, and other lexical classes with NLTagger.

func tagPartsOfSpeech(in text: String) -> [(String, NLTag)] {
    let tagger = NLTagger(tagSchemes: [.lexicalClass])
    tagger.string = text

    var results: [(String, NLTag)] = []
    let range = text.startIndex..<text.endIndex
    let options: NLTagger.Options = [.omitPunctuation, .omitWhitespace]

    tagger.enumerateTags(in: range, unit: .word, scheme: .lexicalClass, options: options) { tag, tokenRange in
        if let tag {
            results.append((String(text[tokenRange]), tag))
        }
        return true
    }
    return results
}

Common Tag Schemes

Named Entity Recognition

Extract people, places, and organizations.

func extractEntities(from text: String) -> [(String, NLTag)] {
    let tagger = NLTagger(tagSchemes: [.nameType])
    tagger.string = text

    var entities: [(String, NLTag)] = []
    let options: NLTagger.Options = [.omitPunctuation, .omitWhitespace, .joinNames]

    tagger.enumerateTags(
        in: text.startIndex..<text.endIndex,
        unit: .word,
        scheme: .nameType,
        options: options
    ) { tag, tokenRange in
        if let tag, tag != .other {
            entities.append((String(text[tokenRange]), tag))
        }
        return true
    }
    return entities
}
// NLTag values: .personalName, .placeName, .organizationName

Sentiment Analysis

Score text sentiment from -1.0 (negative) to +1.0 (positive).

func sentimentScore(for text: String) -> Double? {
    let tagger = NLTagger(tagSchemes: [.sentimentScore])
    tagger.string = text

    let (tag, _) = tagger.tag(
        at: text.startIndex,
        unit: .paragraph,
        scheme: .sentimentScore
    )
    return tag.flatMap { Double($0.rawValue) }
}

Text Embeddings

Measure semantic similarity between words or sentences with NLEmbedding.

func wordSimilarity(_ word1: String, _ word2: String) -> Double? {
    guard let embedding = NLEmbedding.wordEmbedding(for: .english) else { return nil }
    return embedding.distance(between: word1, and: word2, distanceType: .cosine)
}

func findSimilarWords(to word: String, count: Int = 5) -> [(String, Double)] {
    guard let embedding = NLEmbedding.wordEmbedding(for: .english) else { return [] }
    return embedding.neighbors(for: word, maximumCount: count, distanceType: .cosine)
}

Sentence embeddings compare entire sentences.

func sentenceSimilarity(_ s1: String, _ s2: String) -> Double? {
    guard let embedding = NLEmbedding.sentenceEmbedding(for: .english) else { return nil }
    return embedding.distance(between: s1, and: s2, distanceType: .cosine)
}

Translation

System Translation Overlay

Show the built-in translation UI with .translationPresentation().

import SwiftUI
import Translation

struct TranslatableView: View {
    @State private var showTranslation = false
    let text = "Hello, how are you?"

    var body: some View {
        Button { showTranslation = true } label: {
            Text(text)
        }
        .buttonStyle(.plain)
        .translationPresentation(
            isPresented: $showTranslation,
            text: text
        )
    }
}

Programmatic Translation

Use .translationTask() for programmatic translations within a view context.

struct TranslatingView: View {
    @State private var translatedText = ""
    @State private var translationErrorMessage: String?
    @State private var configuration: TranslationSession.Configuration?

    var body: some View {
        VStack {
            Text(translatedText)
            Button("Translate") {
                configuration = .init(source: Locale.Language(identifier: "en"),