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New NER Benchmark for Classical Sanskrit Developed

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Padārtha, a novel Named Entity Recognition (NER) benchmark specifically designed for classical Sanskrit texts. This benchmark grounds its annotation schema in the Nyāya-Vaiśeṣika ontological system, a classical Indian philosophical framework, to avoid imposing modern definitions on ancient literature. The benchmark, built upon the Mahābhārata epic, includes over 12,600 annotated entries and a 5,000-verse expert-verified test set, aiming to improve NER accuracy for historical texts. AI

IMPACT This benchmark could improve the accuracy of AI models in understanding and processing classical Sanskrit literature.

RANK_REASON The item describes a new academic benchmark for a specific NLP task (NER) on a historical language corpus. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New NER Benchmark for Classical Sanskrit Developed

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The item describes a new academic benchmark for a specific NLP task (NER) on a historical language corpus. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Sujoy Sarkar, Pretam Ray, Paramhans Shah, Manoj Balaji Jagadeeshan, Akash Gairola, Arjuna S R, Pawan Goyal ·

    Pad\=artha: Ontology-Grounded Fine-Grained NER Benchmark for Classical Sanskrit

    arXiv:2608.29324v1 Announce Type: new Abstract: Annotation schemas are not neutral. When applied to classical literature, tag sets developed for modern journalistic texts impose source-culture definitions on texts they were never designed to describe. We instead ground a schema i…

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