<p>Essentially you would need to train a named entity recognizer (NER) to recognize the names out of the common words.</p>

<p>There are many works that try to use a similar language to the language in question as a pivot to train a full NER model (for example, <a href="https://www.aclweb.org/anthology/D17-1269" rel="nofollow noreferrer"><em>Cheap Translation for Cross-Lingual Named Entity Recognition</em></a>).</p>

<p>Your task might be slightly simpler, as you are interested only in one class: whether it is a named entity or not. But in general it is very similar to this setup.</p>

CC BY-SA 4.0
2019-06-06T21:32:55.633Z
2019-06-07T11:55:55.800Z
2019-06-07T11:55:55.800Z
justhalf
<p>If an NLP system processes a text containing proper nouns like names, trade marks, etc. without knowing anything about the language (ie no lexicon), is it possible to recognise them?</p>

<natural-language-processing>
How to distinguish between proper nouns and other words in NLP?
user8426627
# How to distinguish between proper nouns and other words in NLP?

(Asked by: username_0 on 2019-06-06)

If an NLP system processes a text containing proper nouns like names, trade marks, etc. without knowing anything about the language (ie no lexicon), is it possible to recognise them?

**Tags:** natural-language-processing


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## 1 answers

### Answer by username_1 on 2019-06-06. Score: 1

Essentially you would need to train a named entity recognizer (NER) to recognize the names out of the common words.

There are many works that try to use a similar language to the language in question as a pivot to train a full NER model (for example, [*Cheap Translation for Cross-Lingual Named Entity Recognition*](https://www.aclweb.org/anthology/D17-1269)).

Your task might be slightly simpler, as you are interested only in one class: whether it is a named entity or not. But in general it is very similar to this setup.


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