Community project / Applications and workflows

JevSpan

Zero-shot named entity recognition for Chinese and English text: code splits the text at punctuation and enumerates candidate windows with exact character offsets, Jev answers Choice questions that nominate, verify, and fix the boundary of each entity, and every result keeps its probability and a decision trace (CLI, Python library, and local web UI; MIT). Its authors report 73.7 average strict F1 on 200-sentence samples of 12 public NER benchmarks with jev-1.13.0, with aggregate results committed; input text is sent to TypeSafe, and an entity that no candidate window covers cannot be found.

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  Jevtown

  Town of 10,000 computed personas that reads a post, listing, product, or headline: one opening request scores the text against about 60 audience attributes, 83 for a listing or a product, plus seven moderation questions, and plans the first wave of 600 readers; batched Choice questions then return each persona's reaction, and the text reaches the next wave only while glad reactions outweigh sorry ones. Also returns the audience by interest, job, age, city, and budget, the question buyers would ask a listing first, and a demand curve over an author-set price ladder. Personas are computed from their id rather than written by a model, and each reaction is sampled from the returned probabilities with a fixed seed, so the result is a simulation of a typed audience and not a forecast of real behaviour; open source (MIT), no sign-in, runs on a TypeSafe or OpenRouter key.

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  Lossless Rewrite

  Helps AI say the same thing in fewer words: choose which ideas must stay, let your model rewrite, and use Jev to check for lost meaning and guide repairs; available as a local editor and CLI; MIT licensed.

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  Paper Radar

  GitHub Action that sends paper titles, abstracts, and categories from arXiv, bioRxiv, or RSS to Jev for interest and contribution-type judgments, then applies code-owned thresholds to publish a page and RSS feed; a committed 50-paper run reports 5 seconds and $0.001957 with jev-1.13.0, while calibration requires the reader's own labels and the judgments do not inspect full papers.

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