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
- 什么是 列表([723, 748))):
- T:随着时间的推移;
- 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)