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New pipeline jaROTE improves temporal expression accuracy in Japanese news for RAG

By PulseAugur Editorial · [1 sources] ·

Researchers have developed jaROTE, a rule-based pipeline designed to address the challenge of omitted temporal expressions in Japanese news articles. This system aims to improve the accuracy of retrieval-augmented generation (RAG) and search systems by converting relative dates (like day-only or month-only mentions) into concrete dates or intervals, using the publication date as context. Experiments on Japanese news corpora show that jaROTE performs effectively, offering a fast and cost-efficient alternative to large language models while enhancing time-constrained lexical retrieval. AI

IMPACT Enhances the temporal accuracy of RAG systems, potentially improving the reliability of AI-driven information retrieval and generation from news sources.

RANK_REASON Academic paper detailing a new method for NLP task. [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 pipeline jaROTE improves temporal expression accuracy in Japanese news for RAG

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Academic paper detailing a new method for NLP task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Tomoaki Yasuda, Shotaro Ishihara ·

    Reproducing Omitted Temporal Expressions in Japanese News for Retrieval-Augmented Applications

    arXiv:2609.09569v1 Announce Type: new Abstract: News articles often contain omitted temporal expressions, such as day-only or month-only mentions, which must be interpreted with reference to the publication date. When such articles are indexed or processed as standalone text in s…

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