diff --git a/kag/examples/images/kag-knowledge-inspection-diag.png b/_static/images/examples/kag-knowledge-inspection-diag.png similarity index 100% rename from kag/examples/images/kag-knowledge-inspection-diag.png rename to _static/images/examples/kag-knowledge-inspection-diag.png diff --git a/kag/examples/medicine/images/kag-medicine-diag.png b/_static/images/examples/medicine/kag-medicine-diag.png similarity index 100% rename from kag/examples/medicine/images/kag-medicine-diag.png rename to _static/images/examples/medicine/kag-medicine-diag.png diff --git a/kag/examples/riskmining/images/kag-riskmining-data-demo.png b/_static/images/examples/riskmining/kag-riskmining-data-demo.png similarity index 100% rename from kag/examples/riskmining/images/kag-riskmining-data-demo.png rename to _static/images/examples/riskmining/kag-riskmining-data-demo.png diff --git a/kag/examples/riskmining/images/kag-riskmining-diag.png b/_static/images/examples/riskmining/kag-riskmining-diag.png similarity index 100% rename from kag/examples/riskmining/images/kag-riskmining-diag.png rename to _static/images/examples/riskmining/kag-riskmining-diag.png diff --git a/kag/examples/supplychain/images/kag-supplychain-event-demo.png b/_static/images/examples/supplychain/kag-supplychain-event-demo.png similarity index 100% rename from kag/examples/supplychain/images/kag-supplychain-event-demo.png rename to _static/images/examples/supplychain/kag-supplychain-event-demo.png diff --git a/kag/examples/supplychain/images/kag-supplychain-event-diag.gif b/_static/images/examples/supplychain/kag-supplychain-event-diag.gif similarity index 100% rename from kag/examples/supplychain/images/kag-supplychain-event-diag.gif rename to _static/images/examples/supplychain/kag-supplychain-event-diag.gif diff --git a/kag/examples/supplychain/images/kag-supplychain-product-chain-demo-cn.gif b/_static/images/examples/supplychain/kag-supplychain-product-chain-demo-cn.gif similarity index 100% rename from kag/examples/supplychain/images/kag-supplychain-product-chain-demo-cn.gif rename to _static/images/examples/supplychain/kag-supplychain-product-chain-demo-cn.gif diff --git a/kag/examples/supplychain/images/kag-supplychain-product-chain-demo-en.gif b/_static/images/examples/supplychain/kag-supplychain-product-chain-demo-en.gif similarity index 100% rename from kag/examples/supplychain/images/kag-supplychain-product-chain-demo-en.gif rename to _static/images/examples/supplychain/kag-supplychain-product-chain-demo-en.gif diff --git a/kag/examples/supplychain/images/kag-supplychain-schema-diag.gif b/_static/images/examples/supplychain/kag-supplychain-schema-diag.gif similarity index 100% rename from kag/examples/supplychain/images/kag-supplychain-schema-diag.gif rename to _static/images/examples/supplychain/kag-supplychain-schema-diag.gif diff --git a/kag/examples/README.md b/kag/examples/README.md index d5582999..b0cbf125 100644 --- a/kag/examples/README.md +++ b/kag/examples/README.md @@ -316,7 +316,7 @@ The KAG framework provides checkpoint-based resumption functionality. If the tas Currently, OpenSPG-KAG provides the [Knowledge Exploration](https://openspg.yuque.com/ndx6g9/cwh47i/mzq74eaynm4rqx4b) capability in product mode, along with the corresponding API documentation [HTTP API Reference](https://openspg.yuque.com/ndx6g9/cwh47i/qvbgge62p7argtd2). -![KAG Knowledge Inspection Diagram](./images/kag-knowledge-inspection-diag.png) +![KAG Knowledge Inspection Diagram](/_static/images/examples/kag-knowledge-inspection-diag.png) ## 4. Reasoning-based question answering diff --git a/kag/examples/README_cn.md b/kag/examples/README_cn.md index 81b8987d..03305400 100644 --- a/kag/examples/README_cn.md +++ b/kag/examples/README_cn.md @@ -316,7 +316,7 @@ KAG 框架基于 checkpoint 文件提供了断点续跑的功能。如果由于 当前，OpenSPG-KAG 在产品端已提供 [知识探查](https://openspg.yuque.com/ndx6g9/0.6/fw4ge5c18tyfl2yq) 能力，以及对应的 API 文档 [HTTP API Reference](https://openspg.yuque.com/ndx6g9/0.6/zde1yunbb8sncxtv)。 -![KAG Knowledge Inspection Diagram](./images/kag-knowledge-inspection-diag.png) +![KAG Knowledge Inspection Diagram](/_static/images/examples/kag-knowledge-inspection-diag.png) ## 4. 推理问答 diff --git a/kag/examples/medicine/README.md b/kag/examples/medicine/README.md index 6fbb574b..7470d6d3 100644 --- a/kag/examples/medicine/README.md +++ b/kag/examples/medicine/README.md @@ -5,7 +5,7 @@ This example aims to demonstrate how to extract and construct entities and relations in a knowledge graph based on the SPG-Schema using LLMs. -![KAG Medicine Diagram](./images/kag-medicine-diag.png) +![KAG Medicine Diagram](/_static/images/examples/medicine/kag-medicine-diag.png) ## 1. Precondition diff --git a/kag/examples/medicine/README_cn.md b/kag/examples/medicine/README_cn.md index d8601884..dbd08594 100644 --- a/kag/examples/medicine/README_cn.md +++ b/kag/examples/medicine/README_cn.md @@ -5,7 +5,7 @@ 本示例旨在展示如何基于 schema 的定义，利用大模型实现对图谱实体和关系的抽取和构建到图谱。 -![KAG Medicine Diagram](./images/kag-medicine-diag.png) +![KAG Medicine Diagram](/_static/images/examples/medicine/kag-medicine-diag.png) ## 1. 前置条件 diff --git a/kag/examples/riskmining/README.md b/kag/examples/riskmining/README.md index 92c287b7..18004e67 100644 --- a/kag/examples/riskmining/README.md +++ b/kag/examples/riskmining/README.md @@ -7,7 +7,7 @@ **Keywords**: semantic properties, dynamic multi-classification of entities, knowledge application in the context of hierarchical business knowledge and factual data. -![KAG RiskMining Diagram](./images/kag-riskmining-diag.png) +![KAG RiskMining Diagram](/_static/images/examples/riskmining/kag-riskmining-diag.png) ## 1. Precondition @@ -69,7 +69,7 @@ knext reasoner execute --dsl "${ql}" #### Scenario 1: Semantic attributes vs text attributes -![KAG RiskMining Data Demo](./images/kag-riskmining-data-demo.png) +![KAG RiskMining Data Demo](/_static/images/examples/riskmining/kag-riskmining-data-demo.png) MobilePhone: "standard attribute" vs "text attribute". diff --git a/kag/examples/riskmining/README_cn.md b/kag/examples/riskmining/README_cn.md index b1b64954..50609d0c 100644 --- a/kag/examples/riskmining/README_cn.md +++ b/kag/examples/riskmining/README_cn.md @@ -5,7 +5,7 @@ **关键词**：语义属性，实体动态多分类，面向业务知识和事实数据分层下的知识应用 -![KAG RiskMining Diagram](./images/kag-riskmining-diag.png) +![KAG RiskMining Diagram](/_static/images/examples/riskmining/kag-riskmining-diag.png) ## 1. 前置条件 @@ -67,7 +67,7 @@ knext reasoner execute --dsl "${ql}" #### 场景 1：语义属性对比文本属性 -![KAG RiskMining Data Demo](./images/kag-riskmining-data-demo.png) +![KAG RiskMining Data Demo](/_static/images/examples/riskmining/kag-riskmining-data-demo.png) 电话号码：标准属性 vs 文本属性。 diff --git a/kag/examples/supplychain/README.md b/kag/examples/supplychain/README.md index 62176e6f..7694d6e5 100644 --- a/kag/examples/supplychain/README.md +++ b/kag/examples/supplychain/README.md @@ -13,11 +13,11 @@ This example is based on the SPG framework to construct an industry chain enterp Please refer to the document for knowledge modeling: [Schema of Enterprise Supply Chain Knowledge Graph](./schema/README.md), As shown in the example below: -![KAG SupplyChain Schema Diagram](./images/kag-supplychain-schema-diag.gif) +![KAG SupplyChain Schema Diagram](/_static/images/examples/supplychain/kag-supplychain-schema-diag.gif) Concept knowledge maintains industry chain-related data, including hierarchical relations, supply relations. Entity instances consist of only legal representatives and transfer information. Company instances are linked to product instances based on the attributes of the products they produce, enabling deep information mining between company instances, such as supplier relationships, industry peers, and shared legal representatives. By leveraging deep contextual information, more credit assessment factors can be provided. -![KAG SupplyChain Event Diagram](./images/kag-supplychain-event-diag.gif) +![KAG SupplyChain Event Diagram](/_static/images/examples/supplychain/kag-supplychain-event-diag.gif) Within the industrial chain, categories of product and company events are established. These categories are a combination of indices and trends. For example, an increase in price consists of the index "价格" (price) and the trend "上涨" (rising). Causal knowledge sets the events of a company's profit decrease and cost increase due to a rise in product prices. When a specific event occurs, such as a significant increase in rubber prices, it is categorized under the event of a price increase. As per the causal knowledge, a price increase in a product leads to two event types: a decrease in company profits and an increase in company costs. Consequently, new events are generated:"三角\*\*轮胎公司成本上涨事件" and "三角\*\*轮胎公司利润下跌". diff --git a/kag/examples/supplychain/README_cn.md b/kag/examples/supplychain/README_cn.md index e0c933a1..e4f226e5 100644 --- a/kag/examples/supplychain/README_cn.md +++ b/kag/examples/supplychain/README_cn.md @@ -13,11 +13,11 @@ 建模参考 [基于 SPG 建模的产业链企业图谱](./schema/README_cn.md)，如下图示意。 -![KAG SupplyChain Schema Diagram](./images/kag-supplychain-schema-diag.gif) +![KAG SupplyChain Schema Diagram](/_static/images/examples/supplychain/kag-supplychain-schema-diag.gif) 概念知识维护着产业链相关数据，包括上下位层级、供应关系；实体实例仅有法人代表、转账信息，公司实例通过生产的产品属性和概念中的产品节点挂载，实现了公司实例之间的深度信息挖掘，例如供应商、同行业、同法人代表等关系。基于深度上下文信息，可提供更多的信用评估因子。 -![KAG SupplyChain Event Diagram](./images/kag-supplychain-event-diag.gif) +![KAG SupplyChain Event Diagram](/_static/images/examples/supplychain/kag-supplychain-event-diag.gif) 产业链中建立了产品和公司事件类别，该类别属于指标和趋势的一种组合，例如价格上涨，是由指标：价格，趋势：上涨两部分构成。