juliadollis/stf_regex_ner_pierre_36

该数据集包含法律相关的文本数据，主要特征包括全文内容（inteiro_teor）、决策日期（dataDecisao）、发布日期（dataPublicacao）、决策内容（decisao）、类别描述（descricaoClasse）、摘要（ementa）、ID（id）、引用的判例（jurisprudenciaCitada）、报告法官（ministroRelator）、审判机构名称（nomeOrgaoJulgador）、案件编号（numeroProcesso）、法律参考（referenciasLegislativas）、类别缩写（siglaClasse）、决策类型（tipoDeDecisao）、标题（titulo）、类似判决（acordaosSimilares）、当事人列表文本（partes_lista_texto）、案件主题（temaProcs）、全文内容的正则表达式（inteiro_teor_regex）以及命名实体识别（NER）信息。NER部分进一步细分为判例（JURISPRUDENCIA）、立法（LEGISLACAO）、地点（LOCAL）、组织（ORGANIZACAO）、人物（PESSOA）和时间（TEMPO）。数据集包含一个训练集，包含1000个样本，占用80477646字节。

This dataset contains legal-related text data, with main features including full text content (inteiro_teor), decision date (dataDecisao), publication date (dataPublicacao), decision content (decisao), class description (descricaoClasse), summary (ementa), ID (id), cited jurisprudence (jurisprudenciaCitada), reporting judge (ministroRelator), name of the adjudicating body (nomeOrgaoJulgador), case number (numeroProcesso), legislative references (referenciasLegislativas), class abbreviation (siglaClasse), type of decision (tipoDeDecisao), title (titulo), similar judgments (acordaosSimilares), list of parties text (partes_lista_texto), case themes (temaProcs), regular expression of full text content (inteiro_teor_regex), and named entity recognition (NER) information. The NER section is further divided into jurisprudence (JURISPRUDENCIA), legislation (LEGISLACAO), location (LOCAL), organization (ORGANIZACAO), person (PESSOA), and time (TEMPO). The dataset includes a training set with 1000 samples, occupying 80477646 bytes.