Prompt Details
Model
Completion - GPT-3.5 (text-davinci-003)
Token size
155 ($0.00310 / call)
Example input
For evaluating machine-generated texts, automatic methods hold the promise of avoiding collection of human judgments, which can be expensive and time-consuming. The most common automatic metrics, like BLEU and ROUGE, depend on exact word matching, an inflexible approach for measuring semantic similarity.
Example output
For evaluating machine-generated texts, automatic methods hold the promise of avoiding collection of human judgments, which can be expensive and time-consuming. The most most common automatic metrics, like [BLEU](https://en.wikipedia.org/wiki/BLEU) and [ROUGE](https://en.wikipedia.org/wiki/ROUGE_(metric)), depend on exact word matching, an inflexible approach for measuring [semantic similarity](https://en.wikipedia.org/wiki/Semantic_similarity).
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TEXT-DAVINCI-003
Wikification is the process of identifying the crucial phrases in a document and linking each of them to appropriate articles on Wikipedia based on their context of occurrences. I bet it's gonna save you a lot of time and tremendously improve your productivity. Try this :)
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