Elasticsearch 7.6 introduces language identification to improve search relevance in multilingual corpora, utilizing language-specific analyzers for better tokenization, stemming, and decompounding. Documents are indexed using strategies like language per-field or language per-index, each offering unique benefits and challenges. The language per-field strategy allows for a single index with multiple language fields, facilitating language-specific analysis and boosting, while the language per-index strategy creates separate indices for each language, simplifying queries and scaling. Language identification enhances search accuracy by ensuring terms are analyzed appropriately, but its application to query strings is limited due to their brevity. The choice between indexing strategies depends on factors like management complexity and performance needs. Ultimately, language identification in Elasticsearch enables more precise and relevant multilingual searches, supporting diverse languages and scripts across different contexts.