模型:

opennyaiorg/en_legal_ner_trf

类库:

spaCy

语言:

en

许可:

mit
英文

更新

[作者] "[论文名称]"。[论文细节] [论文链接]

印度法律命名实体识别(NER):使用训练于 spacy 的法律NER在印度法律判决中识别相关命名实体。

分数

Type Score
F1-Score 91.076
Precision 91.979
Recall 90.19
Feature Description
Name en_legal_ner_trf
Version 3.2.0
spaCy >=3.2.2,<3.3.0
Default Pipeline transformer , ner
Components transformer , ner
Vectors 0 keys, 0 unique vectors (0 dimensions)
Sources 1234321 1235321
License MIT
Author 1236321

加载预训练模型

使用pip安装模型

pip install https://huggingface.co/opennyaiorg/en_legal_ner_trf/resolve/main/en_legal_ner_trf-any-py3-none-any.whl

使用预训练NER模型

# Using spacy.load().
import spacy
nlp = spacy.load("en_legal_ner_trf")
text = "Section 319 Cr.P.C. contemplates a situation where the evidence adduced by the prosecution for Respondent No.3-G. Sambiah on 20th June 1984"
doc = nlp(text)

# Print indentified entites
for ent in doc.ents:
     print(ent,ent.label_)

##OUTPUT     
#Section 319 PROVISION
#Cr.P.C. STATUTE
#G. Sambiah RESPONDENT
#20th June 1984 DATE

标签方案

查看标签方案(1个组件的14个标签)
ENTITY BELONGS TO
LAWYER PREAMBLE
COURT PREAMBLE, JUDGEMENT
JUDGE PREAMBLE, JUDGEMENT
PETITIONER PREAMBLE, JUDGEMENT
RESPONDENT PREAMBLE, JUDGEMENT
CASE_NUMBER JUDGEMENT
GPE JUDGEMENT
DATE JUDGEMENT
ORG JUDGEMENT
STATUTE JUDGEMENT
WITNESS JUDGEMENT
PRECEDENT JUDGEMENT
PROVISION JUDGEMENT
OTHER_PERSON JUDGEMENT

作者-出版物

[CITATION DETAILS]