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information-retrieval - 了解 OpenIE 5 输出

问题描述

我使用你的Open IE 5 来提取三元组并得到以下结果，

文本输入
通过称为 LevenbergMarquardt 反向传播算法的算法方法，误差会反复减少。一些 ANN 模型采用监督训练，而其他模型则被称为非监督训练或自组织训练。然而，绝大多数人工神经网络模型使用监督监督训练。训练阶段可能会消耗大量时间。在监督训练中，将人工神经网络的实际输出与期望输出进行比较。训练集包括向网络呈现输入和输出数据。网络调整加权系数，通常从随机集开始，以便下一次迭代将在期望的和实际的 ANN 实际输出之间产生更接近的匹配。训练方法试图最小化所有处理元素的当前错误。

输出

0.89 Context(The training method tries,List([723, 748))):(The training method; tries to minimize; the current errors for all processing elements)
0.95 (the vast majority of ANN models; use; supervisory the supervisory training)
0.88 (others; are referred; as self - organizing training)
0.89 Context(The training method tries,List([717, 742))):(The training method; tries to minimize; the current errors for all processing elements)
0.93 Context(Some ANN models employ The training phase may consume,List([120, 340))):(the error; is decreased; T:repeatedly; T:By the algorithmic approach)
0.94 Context(The training phase may consume,List([310, 340))):(Some ANN models; employ; supervisory training; while others are referred to as self - organizing training)
0.89 Context(The training method tries,List([724, 749))):(The training method; tries to minimize; the current errors for all processing elements)
0.93 Context(The training phase may consume,List([311, 341))):(the vast majority of ANN models; use; supervisory the supervisory training)
0.93 Context(Some ANN models employ The training phase may consume,List([120, 341))):(the error; is decreased; T:repeatedly; T:By the algorithmic approach)
0.94 Context(The training phase may consume,List([311, 341))):(Some ANN models; employ; supervisory training; while others are referred to as none - supervisory training)
0.92 (This global error reduction; is created; T:over time; by continuously modifying the)

谁能帮我理解一下

标签： information-retrievalinformation-extractiontriples

解决方案

为了回答“什么是列表（[723, 748）））：？
我认为这是输入句子中上下文短语的位置/跨度。
T：随着时间的推移；这是将角色标记为时间。即“随着时间的推移”是 SRL 中的时间角色。
在某些情况下，它有 4 个实体，（错误；减少；T：重复；T：通过算法方法）：OpenIE 有时除了通常的三元提取之外还提供 n 元关系提取。

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