The following XML shows a single record produced by news segmentation.
<NewsSegmentationResult>
<id>af4475f5-beb2-401e-bf73-fb494f63af27</id>
<storyText>business secretary says the government will consider co investing
with a Buy on commercial terms <SIL> ...</storyText>
<score>0</score>
<terms>
<term>
<text>Buy</text>
<weight>170</weight>
</term>
<term>
<text>business secretary says</text>
<weight>120</weight>
</term>
<term>
<text>consider co investing</text>
<weight>110</weight>
</term>
<term>
<text>commercial terms</text>
<weight>90</weight>
</term>
...
</terms>
<type>Short story</type>
</NewsSegmentationResult>
The record contains the following elements:
storyText contains the text extracted from the video. The text is extracted from the audio by speech-to-text. Words are then combined into segments by the text segmentation task. News Segmentation analyzes the segments and combines one or more segments into a result that represents a story, short story, or video with no topic.score is an integer from 0 to 100 that indicates the consistency between the terms in each segment that makes up the storyText. terms/term/text element contains a key term extracted from the text.terms/term/weight element contains the weight of the associated term. You might want to use this weight when building a term cloud. The weights are relative to the other terms in the story, and cannot be compared across stories.type element specifies whether the news segmentation task has classified the segment as a Story, Short Story, or a segment with No topic.|
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