Multilingual AI/ML training data, sorted by relevance, entity and geolocation

We run our models on large numbers of content links to assess their suitability for training and testing data. We filter and sort the results by relevance (e.g. suitability for training, inferred human value), by entity (e.g. a specific country, business, or industry sector) and by geolocation (e.g. a specific city, county, continent). Our datasets can run from several thousand rows to many millions of rows of data. We can also provide various metadata signals with the output for additional fine-tuning during and after training.

搜集汇总

背景与挑战

背景概述

该数据集提供多语言AI/ML训练数据，通过相关性、实体和地理位置进行筛选排序，规模从数千到数百万行，并可附带元数据以支持训练微调。