Removing Ambiguity in Language Detection
Question
Your organization has a requirement to analyze documents that are written in multiple different languages.
You are tasked to detect the language using the Detect Language API of Text Analytics in Azure.
While you analyze the JSON output for the documents, you realize that the results are ambiguous.
Here is an example of the JSON output:
{ "documents": [ { "id": "1", "detectedLanguage": { "name": "(Unknown)", "iso6391Name": "(Unknown)", "confidenceScore": 0.0 }, "warnings": [] } ], } Which input parameter would you use in your code to remove this ambiguity in detecting language when you identify the origin of the text is not known or same words are used in the different languages?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: C.
Option A is incorrect because detectedLanguage is the output parameter used in the JSON output of the Detect Language API of Text Analytics.
It contains the name, ISO code and confidence score of the language.
Option B is incorrect because iso6391Name is the output parameter used in the JSON output of the Detect Language API of Text Analytics.
It provides the ISO code of the language such as “en” for English language.
Option C is correct because countryHint is the input parameter that is helpful in such a scenario where the origin of the text is not known.
Here is a sample code in that countryHint is added and it provides additional context to avoid ambiguity.
In the output, confidence score for "iso6391Name":"fr" is 1.0 and "iso6391Name":"en" is observed to be 0.63
<pre class="brush:java;">{
"documents": [
{
"id": "1",
"text": "impossible"
},
{
"id": "2",
"text": "impossible",
"countryHint": "fr"
}
]
}
</pre>
Option D is incorrect because name is the output parameter used in the JSON output of the Detect Language API of Text Analytics.
To learn more about language detection, use the link given below:
When analyzing documents written in multiple different languages using the Detect Language API of Text Analytics in Azure, it is possible to encounter ambiguous results. This could happen, for example, when the origin of the text is not known, or when the same words are used in different languages.
To remove this ambiguity and improve the accuracy of language detection, the 'countryHint' input parameter can be used. This parameter specifies a hint about the country or region where the text originated. This can help the Text Analytics API narrow down the list of possible languages and improve the accuracy of language detection.
For example, suppose you have a document that contains text in Spanish and Portuguese, and you do not know the origin of the text. Without the 'countryHint' parameter, the Text Analytics API may detect both Spanish and Portuguese with similar confidence scores, which would lead to ambiguous results. However, if you provide a 'countryHint' of "BR" (for Brazil) or "ES" (for Spain), the Text Analytics API can use this information to bias its language detection towards the specified country or region, and thus improve the accuracy of its results.
In the given JSON output, the detected language has been reported as "(Unknown)", with a confidence score of 0.0. This means that the Text Analytics API was unable to confidently determine the language of the input text. In this case, using the 'countryHint' parameter alone may not be sufficient to improve the accuracy of language detection. Other options to consider include using a larger sample of text, or using additional context or metadata to inform the language detection process.
