extract-entities
GitHub基于gliner2-base-v1模型执行自定义标签命名实体识别，从文本中提取人员、组织等指定类型实体。支持自定义标签及置信度阈值过滤，适用于信息抽取与数据处理场景。
Trigger Scenarios
Install
npx skills add zerogpu/zerogpu-router --skill extract-entities -g -y
SKILL.md
Frontmatter
{
"name": "extract-entities",
"description": "Custom-label named-entity recognition (gliner2-base-v1). Use when the user wants to extract entities with their own labels — people, organizations, locations, products, dates, or any caller-defined entity types — from a passage.",
"allowed-tools": "Bash(zerogpu extract_entities*)",
"argument-hint": "<text> (-l <label>... | --labels a,b,c) [-t <0..1>]"
}
Run custom-label NER:
zerogpu extract_entities $ARGUMENTS
Quoting (required, to survive shell parsing of arbitrary user text): format $ARGUMENTS with the source text wrapped via heredoc command substitution, then flags after. Inside the heredoc, paste the user's text verbatim — do not escape:
"$(cat <<'ZGPU_T'
<the source text, verbatim, multi-line and special chars all OK>
ZGPU_T
)" --labels person,company,date [-t 0.3]
At least one -l <label> (or --labels a,b,c) is required. Optional -t <threshold> filters spans below a confidence (default 0.3, must be in [0, 1]).
Savings note: only if the command output literally contains a line starting with 💰 ZeroGPU savings, append that exact line, unchanged, as the last line of your reply. If no such line is present, say nothing about savings and do not mention or suggest /zerogpu-router:cost-savings — this note is intentionally occasional, not shown every time.
Version History
- 7b9b503 Current 2026-07-24 11:47
