LLMに基づくインクリメンタル知識グラフ構築のための優れたツール：itext2kg
iText2KGは、科学論文、ウェブサイト、履歴書のグラフィカルな変換など、さまざまなシナリオにプラグアンドプレイで対応し、既存のベースラインよりも優れたパフォーマンスを発揮します。
特徴
1、あなたは新しいドキュメントに応じてナレッジグラフを更新することができます、新しい情報は、既存の構造に統合される
2、特定のドメインに特化したトレーニングは必要なく、ドメインを横断して知識を抽出できる
3、文書抽出、実体抽出、関係抽出のためのモジュールを含み、抽出された実体と関係が一意であることを保証し、エラーと情報の重複を減らすために解析される。
4、Neo4jデータベースに統合されたエンティティと関係の抽出をサポートし、視覚的なインターフェイスを提供します。
エンティティ関係の抽出
Act like an expert in Information Extraction. If you don’t find the information, keep its place empty in the json. If the text is in English or French, translate it to English.
Question:
# Directives
- Adhere completely to the provided entities list.
- Do not add any entity outside the provided list.
- Extract ONE predicate per subject and object.
- ALL entities in the provided list should have a relation.
Format Instructions:The output should be formatted as a JSON instance that conforms to the JSON schema below.
As an example, for the schema `{"properties": {"foo": {"title": "Foo", "description": "a list of strings", "type": "array", "items": {"type": "string"}},"required": ["foo"]}}`
The object `{"foo": ["bar", "baz"]}` is a well-formatted instance of the schema.
The object `{"properties": {"foo": ["bar", "baz"]}}` is not well-formatted.
Here is the output schema:
```json
{
"properties": {
"relationships": {
"title": "Relationships",
"default": "Given the provided entities and context, try to find the predicates between these entities. They should be chosen carefully to accurately represent the relationship being expressed.",
"type": "array",
"items": {
"$ref": "#/definitions/Relationship"
}
}
},
"definitions": {
"Relationship": {
"title": "Relationship",
"type": "object",
"properties": {
"startNode": {
"title": "Startnode",
"default": "The start entity, found in the entities list",
"type": "string"
},
"endNode": {
"title": "Endnode",
"default": "The end entity, found in the entities list",
"type": "string"
},
"name": {
"title": "Name",
"default": "The predicate between the two entities. The predicate should encode ONE relation.",
"type": "string"
}
}
}
}
}
Answer:
エンティティ関係の抽出 中国語版
充当信息提取专家。如果未找到信息，请在json中保留该位置为空。如果文本是英文或法文，则将其翻译为英文。
<上下文>
问题：
# 指令
- 完全遵循提供的实体列表。
- 不添加任何提供列表之外的实体。
- 每个主题和对象提取一个谓词。
- 所有提供列表中的实体必须有关系。
格式说明：输出应格式化为符合以下JSON模式的JSON实例。
例如，对于模式 `{"properties": {"foo": {"title": "Foo", "description": "a list of strings", "type": "array", "items": {"type": "string"}},"required": ["foo"]}}`
对象 `{"foo": ["bar", "baz"]}` 是符合该模式的格式良好的实例。
对象 `{"properties": {"foo": ["bar", "baz"]}}` 不是格式良好的。
这是输出模式：
```json
{
"properties": {
"relationships": {
"title": "Relationships",
"default": "根据提供的实体和上下文，尝试找出这些实体之间的谓词。应仔细选择以准确表示所表达的关系。",
"type": "array",
"items": {
"$ref": "#/definitions/Relationship"
}
}
},
"definitions": {
"Relationship": {
"title": "Relationship",
"type": "object",
"properties": {
"startNode": {
"title": "Startnode",
"default": "起始实体，见于实体列表",
"type": "string"
},
"endNode": {
"title": "Endnode",
"default": "结束实体，见于实体列表",
"type": "string"
},
"name": {
"title": "Name",
"default": "两个实体之间的谓词。谓词应编码一个关系。",
"type": "string"
}
}
}
}
}
答案：
抽出主体
Act like an expert in Information Extraction. If you don’t find the information, keep its place empty in the json. If the text is not in English or French, translate it to English.
Question:
Format Instructions:The output should be formatted as a JSON instance that conforms to the JSON schema below.
As an example, for the schema `{"properties": {"foo": {"title": "Foo", "description": "a list of strings", "type": "array", "items": {"type": "string"}},"required": ["foo"]}}`
The object `{"foo": ["bar", "baz"]}` is a well-formatted instance of the schema.
The object `{"properties": {"foo": ["bar", "baz"]}}` is not well-formatted.
Here is the output schema:
```json
{
"properties": {
"entities": {
"title": "Entities",
"default": "All the entities presented in the context. The entities should encode ONE concept.",
"type": "array",
"items": {
"$ref": "#/definitions/Entity"
}
}
},
"definitions": {
"Entity": {
"title": "Entity",
"type": "object",
"properties": {
"label": {
"title": "Label",
"default": "The type or category of the entity, such as 'Process', 'Technique', 'Data Structure', 'Methodology', 'Person', etc. This field helps in classifying and organizing entities within the knowledge graph.",
"type": "string"
},
"name": {
"title": "Name",
"default": "The specific name of the entity. It should represent a single, distinct concept and must not be an empty string. For example, if the entity is a 'Technique', the name could be 'Neural Networks'.",
"type": "string"
}
}
}
}
}
Answer:
エンティティの抽出 中国語版
扮演一个信息提取专家。如果找不到相关信息，请在JSON中将对应位置保留为空。如果文本不是英语或法语，请将其翻译成英语。
问题：
格式说明：输出应该格式化为符合以下JSON模式的JSON实例。
例如，对于模式`{"properties": {"foo": {"title": "Foo", "description": "a list of strings", "type": "array", "items": {"type": "string"}},"required": ["foo"]}}`
对象`{"foo": ["bar", "baz"]}`是该模式的格式正确的实例。
对象`{"properties": {"foo": ["bar", "baz"]}}`格式不正确。
以下是输出模式：
```json
{
"properties": {
"entities": {
"title": "实体",
"default": "上下文中出现的所有实体。每个实体应该表示一个独立的概念。",
"type": "array",
"items": {
"$ref": "#/definitions/Entity"
}
}
},
"definitions": {
"Entity": {
"title": "实体",
"type": "object",
"properties": {
"label": {
"title": "标签",
"default": "实体的类型或类别，如'过程'、'技术'、'数据结构'、'方法论'、'人物'等。此字段有助于在知识图谱中对实体进行分类和组织。",
"type": "string"
},
"name": {
"title": "名称",
"default": "实体的具体名称。它应代表一个单一的、明确的概念，且不能为空字符串。例如，如果实体类型是'技术'，名称可能是'神经网络'。",
"type": "string"
}
}
}
}
}
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