Ebisu - JF-TE - F1: leaderboard

Evaluates Japanese financial implicit commitment recognition (JF-ICR) and terminology extraction (JF-TE). This is the paper v1 result table, whose stated generation limit is 1,024; current repository task defaults differ. JF-ICR uses accuracy, JF-TE uses maximal-term F1 and hit rates at 1/5/10, and the mean combines five metrics. Published fractions are converted to percentages. Explicit zero scores are retained; malformed predictions can receive zero under the public evaluator. Source-specified dated checkpoints are retained. This series reports Ebisu - JF-TE - F1 using Maximal-Term F1 (%).

Metric: Maximal-Term F1 (%). Source: arxiv.org. Saturation forecast: Around February 2027. 22 models tracked.

Top models

#ModelScoreOverall rank
1Kimi K243.96#252
2Llama 3.3 70B Instruct43.7#541
3Claude Sonnet 4.543.62#148
4Qwen 3 235B A22B 2507 Instruct FP843.55#234
5Qwen 2.5 32B Instruct41.37#509
6Llama 4 Scout41.33#648
7Llama-3.3-Swallow-70B-Instruct-v0.440.7#540
8GPT-4o39.97#357
9Ministral-3-14B-Instruct-251237.56#625
10DeepSeek V3.136.53#275
11Qwen 3 32B28.6#449
12Qwen 3 14B20.38#542
13Qwen-14B16.13#1153
14Qwen 3 8B5.48#678

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=ebisu-jf-te-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.