
A multilingual evaluation test set for Northeast Indian languages containing 500 deduplicated sentences per language across Assamese, Garo, Khasi, Kokborok, Meitei, Mizo, Nagamese, Nyishi, and Pnar for benchmarking low-resource language models.
Northeast Languages Test Set is a multilingual evaluation dataset developed by MWire Labs for benchmarking language models on low resource Northeast Indian languages. The dataset contains 500 deduplicated test sentences per language across Assamese Garo Khasi Kokborok Meitei Mizo Nagamese Nyishi and Pnar totaling 4500 evaluation samples. The dataset was created for multilingual language model evaluation and was used in the NE BERT paper for perplexity benchmarking across Northeast Indian languages. All test sentences were extracted from newer corpora not included in NE BERT training data and were deduplicated against the training corpus to reduce train test leakage. The dataset supports evaluation of multilingual NLP systems language models tokenizers embedding models and cross lingual transfer methods for low resource Indian languages. The included languages span Tibeto Burman Indo Aryan and Austroasiatic language families representing one of the most linguistically diverse regions of India. This resource is intended to support research benchmarking and development of AI systems for underserved Indian languages and regional language technologies.
This Dataset Is Designed For Evaluating Multilingual Language Models And Nlp Systems On Low-resource Northeast Indian Languages. The Dataset Supports Benchmarking Tasks Such As Perplexity Evaluation, Language Modeling, Tokenization Analysis, Multilingual Representation Learning, And Cross-lingual Evaluation. All Sentences Were Extracted From Newer Corpora Outside The Ne-bert Training Data, Deduplicated Against The Training Corpus, And Randomly Sampled To Ensure Linguistic Diversity And Reduced Train-test Leakage. The Dataset Was Used In The Ne-bert Paper For Multilingual Language Model Evaluation Across Nine Northeast Indian Languages Spanning Tibeto-burman, Indo-aryan, And Austroasiatic Language Families. The Resource Is Intended To Support Research, Benchmarking, And Development Of Ai Systems For Underserved Indian Languages.
Attribution 4.0 International (CC BY- 4.0)
© 2026 - Copyright AIKosh. All rights reserved.