github issue fix

Author: mrbullwinkle

articles/cognitive-services/openai/concepts/prompt-engineering.md

@@ -75,10 +75,10 @@ GPT models can also handle primary content that is structured. In the example be
 
 Successful prompts often rely on the practice of “one-shot” or “few-shot” learning. This refers to the inclusion of one or more examples of the desired behavior of the model, typically by including input and output pairs. This is not learning in the sense that the model is permanently changed, but rather that the examples better condition the model to respond as desired for only the current inference. The use of prompts with no examples is sometimes referred to as “zero-shot” learning. Please note that with the Chat Completion API few-shot learning examples are typically added to the messages array in the form of example user/assistant interactions after the initial system message.
 
-| Learning Type| Prompt| Completion|
-|------------------------------------- |-------|-----------|
-| Headline: Coach confident injury won't derail Warriors<br>Topic:| The coach is confident that the injury won't derail the Warriors' season. The team is still focused on their goals and that they will continue to work hard to achieve them.|
-| Headline: Twins' Correa to use opt-out, test free agency<br>Topic: Baseball<br>Headline: Qatar World Cup to have zones for sobering up<br>Topic: Soccer<br>Headline: Yates: Fantasy football intel for Week 6<br>Topic: Football<br>Headline: Coach confident injury won't derail Warriors<br>Topic: | Basketball |
+| Learning Type|  Prompt| Completion|
+|------------------------------------- |-------|-----|
+| Zero-shot | Headline: Coach confident injury won't derail Warriors<br>Topic:| The coach is confident that the injury won't derail the Warriors' season. The team is still focused on their goals and that they will continue to work hard to achieve them.|
+| One-shot | Headline: Twins' Correa to use opt-out, test free agency<br>Topic: Baseball<br>Headline: Qatar World Cup to have zones for sobering up<br>Topic: Soccer<br>Headline: Yates: Fantasy football intel for Week 6<br>Topic: Football<br>Headline: Coach confident injury won't derail Warriors<br>Topic: | Basketball |
 
 The example above illustrates the utility of few-shot learning. Without the examples, the model seems to be guessing at the desired behavior, while the examples cleanly show the model how to operate. This also demonstrates the power of the model, it can infer the category of label that is wanted, even without a ‘basketball’ label in the examples.