1. A translation method comprising: receiving an input query in a source language; and outputting a target query, the target query being identified from a set of candidate target queries, each target query being based on a translation of the input query into a target language, different from the source language, with a machine translation system which includes a reranking model for ranking the candidate target queries, which has been trained by a method which includes: for each of a plurality of training queries in the source language, translating the training query in the source language into the target language to generate translated queries which are each a translation of the respective training query; for each of the translated queries: computing a feature representation of the translated query; retrieving a set of annotated documents from a document collection in response to the translated query, the documents in the retrieved set of annotated documents including annotations that are based on responsiveness of each of the documents to each of the training queries, and computing a precision score for the translated query based on relevance scores of the retrieved documents in the set of annotated documents, each of the relevance scores being based on the annotations of the documents in the retrieved set of annotated documents; and learning feature weights for the reranking model based on the precision scores and feature representations of the translated queries.