Overview
News API v3 translation features let you search across language barriers and retrieve translated content. This guide explains how to use these capabilities effectively with practical examples.Prerequisites
- An active subscription with the NLP plan or higher
- A valid API key with appropriate permissions
Key translation capabilities
News API v3 offers comprehensive translation features:- Search in translated content: Find articles using English keywords even when the original content is in another language.
- Cross-language entity recognition: Search for organizations, people, and locations using English entity names across all languages.
- Retrieve translated fields: Include English translations and NLP data in API responses.
- Global content coverage: Combine original and translated search for maximum reach.
Search in translations
Available search options
To search within translated content, use thesearch_in
parameter with one of
the following options:
Option | Description |
---|---|
title_translated | Search only in translated titles |
content_translated | Search only in translated content |
summary_translated | Search only in translated summaries |
title_content_translated | Search in both translated titles and content |
You can specify a maximum of two options in the
search_in
parameter.Entity search in translations
You can search for named entities within English translations of non-English articles, expanding entity search coverage to 100% (all content via translations). Available entity parameters:PER_entity_name
: Person names (e.g., “Donald Trump”, “Emmanuel Macron”)ORG_entity_name
: Organization names (e.g., “European Union”, “United Nations”, “Federal Reserve”)LOC_entity_name
: Location names (e.g., “United States”, “United Kingdom”)MISC_entity_name
: Other entities (events, products, etc.)
AND
, OR
, NOT
) and
proximity search with NEAR
.
Translation fields in responses
When using translation features, these fields appear in responses: Basic translation fields:title_translated_en
: English translation of the article titlecontent_translated_en
: English translation of the article content
include_nlp_data
is true
):
nlp.summary_translated
: Brief AI-generated summary of the translationnlp.translation_ner_PER
: Person entities extracted from English translationsnlp.translation_ner_ORG
: Organization entities extracted from English translationsnlp.translation_ner_LOC
: Location entities extracted from English translationsnlp.translation_ner_MISC
: Miscellaneous entities extracted from English translations
Field | Description |
---|---|
ner_PER , ner_ORG , ner_LOC , ner_MISC | Entities extracted from original content |
translation_ner_PER , translation_ner_ORG , translation_ner_LOC , translation_ner_MISC | Entities extracted from English translations |
Use case 1: Comprehensive multilingual coverage
Scenario: You want maximum global coverage of climate change discussions, capturing both English and non-English articles discussing the topic. Solution: Search in original and translated fields simultaneously and omit thelang
parameter to achieve complete coverage. To ensure better quality,
exclude duplicates. If needed, include NLP data.
Response example
Response example
- English articles with the original title or content containing “climate change” or “global warming”.
- Non-English articles where the English translation contains these terms.
Use case 2: Tracking international organizations across languages
Scenario: You monitor European Union policy coverage across specific countries. You want to find all articles mentioning the EU, but original languages use different names (Union européenne, Unión Europea, etc.). Solution: Combine keyword search with entity recognition in translations to find organization mentions using standardized English entity names.Use case 3: Global trade policy monitoring
Scenario: You’re monitoring how countries report on US tariff policies and changes in trade developments. Solution: Combine multiple entity types with location filtering to monitor global coverage of trade events.Best practices
- Start simple: Begin with a basic keyword search in original articles and
English translations
(
"search_in": "title_content,title_content_translated",
) before adding entity recognition and complex filtering. - Use precise queries: For organizations and locations, use official
English names in quotes (
"\"European Union\""
) and combine entities with boolean operators (OR
,AND
) for flexible matching. - Target strategically: When monitoring international coverage, use the
countries
parameter to focus on specific regions rather than searching globally. - Monitor translation quality: Translation accuracy varies by source language and content complexity - verify important findings in original content when possible.
Limitations
- Search in translations is only available for English translations.
- Translation features are only available in the NLP subscription plans.
- English translations are available for content from March 12, 2025, onwards.