10-of-my-most-popular-text-to-image-series-prompts-78b0897e
generate a bunch of images, then you curate the results to handpick the best ones
Akkadian noun analyzer using regex-based feature extraction. Use when working with ancient languages, linguistic analysis, or building morphological analyzers for historical languages.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install hhhh124hhhh/akkadian-noun-analyzerExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Hello r/LanguageTechnology,
I'm not as familiar with statistics as I am with formal linguistics, so...
Hello r/LanguageTechnology,
I'm not as familiar with statistics as I am with formal linguistics, so I apologize if this comes across as overly simple. I've been working on an Akkadian noun analyzer. It uses regexes to extract features from surface forms. Example:
{
r"\w+[^t]um?$": {
'type':'nominal_noun',
'gender':'masculine',
'number':'singular',
'case':'nominative',
'state':'governed'
}
I hit a wall with zero-marking, as nouns can be either in the absolute or construct states, as seen here:
r"\w+[^āīēaie]$": {
'type':'nominal_noun',
'gender':'masculine',
'number':'singular',
'case':'nominative',
'state':'absolute/construct'
}
Since the state is unknown, it's left as "absolute/construct".
I have a disambiguator function which takes each word's (words are objects, by the way) feature structures in a list and checks for certa
Skill generated by Clawdbot
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# 通用 Prompt Skill
## 描述
Hello r/LanguageTechnology,
I'm not as familiar with statistics as I am with formal linguistics, so...
## 类型
- 类型: 通用
- 评分: 60/100
## Prompt
```
Hello r/LanguageTechnology,
I'm not as familiar with statistics as I am with formal linguistics, so I apologize if this comes across as overly simple. I've been working on an Akkadian noun analyzer. It uses regexes to extract features from surface forms. Example:
{
r"\w+[^t]um?$": {
'type':'nominal_noun',
'gender':'masculine',
'number':'singular',
'case':'nominative',
'state':'governed'
}
I hit a wall with zero-marking, as nouns can be either in the absolute or construct states, as seen here:
r"\w+[^āīēaie]$": {
'type':'nominal_noun',
'gender':'masculine',
'number':'singular',
'case':'nominative',
'state':'absolute/construct'
}
Since the state is unknown, it's left as "absolute/construct".
I have a disambiguator function which takes each word's (words are objects, by the way) feature structures in a list and checks for certa
```
## 来源信息
- 来源: reddit
- 原始链接: https://www.reddit.com/r/LanguageTechnology/comments/1qfe2tv/statistical_nlp_question_on_bayesian/
- 作者: metalmimiga27
- 互动: 0 赞
## 元数据
- 收集时间: 2026-01-30T20:48:50.626829
- Prompt 类型: 通用
- 质量分数: 60/100
---
*Skill generated by Clawdbot*generate a bunch of images, then you curate the results to handpick the best ones
generate a bunch of images, then you curate the results to handpick the best ones
Productivity system based on Maya calendar with 13 natural tones for project management and personal development
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.