langdetect | Statistical language detection with 50 profiles
kandi X-RAY | langdetect Summary
kandi X-RAY | langdetect Summary
This is a uncomplete github version of the code hosted here I added mavenification and better/simpler resource loading. I intend to improve the library in the future. Work can be done to improve performance, and part of the original lib is not included. If you use maven, this project is hosted at. To import this artifact add this to your dependencies.
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Top functions reviewed by kandi - BETA
- Loads a language profile from an abstract database file
- Normalize a character
- Close tag
- Adds a character to the dictionary
- Constructs a Detector instance
- Set the smoothing parameter
- Create a Detector
- Constructs a Detector instance with smoothing parameters
- Set the smoothing parameter
- Create a Detector
- Detects language name
- Normalize probabilities
- Cleans the text in the text
- Detects the language detection
- Load profiles
- Adds a profile to the detector
- Sets the prior map of language probabilities
- Removes n - gram n - grams
- Clears the DetectorFactory
- Returns the string for the given key
langdetect Key Features
langdetect Examples and Code Snippets
Community Discussions
Trending Discussions on langdetect
QUESTION
Tika 2.2.3, simple code
...ANSWER
Answered 2022-Mar-14 at 13:53QUESTION
I have a dataset of tweets that contains tweets mainly from English but also have several tweets in Indian Languages (such as Punjabi, Hindi, Tamil etc.). I want to keep only English language tweets and remove rows with different language tweets. I tried this [https://stackoverflow.com/questions/67786493/pandas-dataframe-filter-out-rows-with-non-english-text] and it worked on the sample dataset. However, when I tried it on my dataset it showed error:
LangDetectException: No features in text.
Also, I have already checked other question [https://stackoverflow.com/questions/69804094/drop-non-english-rows-pandasand] where the accepted answer talks about this error and mentioned that empty rows might be the reason for this error, so I already cleaned my dataset to remove all the empty rows.
Simple code which worked on sample data but not on original data:
...ANSWER
Answered 2022-Mar-11 at 07:47Use custom function for return True if function detect failed:
QUESTION
I have the following dataframe:
...ANSWER
Answered 2022-Jan-25 at 03:58Use np where(), checking if language has an alphanumeric or not.
QUESTION
I have the following dataframe:
...ANSWER
Answered 2022-Jan-09 at 07:22So, given the following dataframe:
QUESTION
I have a pandas df which has 6 columns, the last one is input_text. I want to remove from df all rows that have non-english text in that column. I would like to use langdetect's detect function.
Some template
...ANSWER
Answered 2021-Jun-01 at 13:31You can do it as below on your df and get all the rows with english text in the input_text column:
QUESTION
How do I provide an OpenNLP model for tokenization in vespa? This mentions that "The default linguistics module is OpenNlp". Is this what you are referring to? If yes, can I simply set the set_language index expression by referring to the doc? I did not find any relevant information on how to implement this feature in https://docs.vespa.ai/en/linguistics.html, could you please help me out with this?
Required for CJK support.
...ANSWER
Answered 2021-May-20 at 16:25Yes, the default tokenizer is OpenNLP and it works with no configuration needed. It will guess the language if you don't set it, but if you know the document language it is better to use set_language (and language=...) in queries, since language detection is unreliable on short text.
However, OpenNLP tokenization (not detecting) only supports Danish, Dutch, Finnish, French, German, Hungarian, Irish, Italian, Norwegian, Portugese, Romanian, Russian, Spanish, Swedish, Turkish and English (where we use kstem instead). So, no CJK.
To support CJK you need to plug in your own tokenizer as described in the linguistics doc, or else use ngram instead of tokenization, see https://docs.vespa.ai/documentation/reference/schema-reference.html#gram
n-gram is often a good choice with Vespa because it doesn't suffer from the recall problems of CJK tokenization, and by using a ranking model which incorporates proximity (such as e.g nativeRank) you'l still get good relevancy.
QUESTION
I am writing some code to perform Named Entity Recognition (NER), which is coming along quite nicely for English texts. However, I would like to be able to apply NER to any language. To do this, I would like to 1) identify the language of a text, and then 2) apply the NER for the identified language. For step 2, I'm doubting to A) translate the text to English, and then apply the NER (in English), or B) apply the NER in the language identified.
Below is the code I have so far. What I would like is for the NER to work for text2, or in any other language, after this language is first recognized:
...ANSWER
Answered 2021-Apr-01 at 18:38Spacy needs to load the correct model for the right language.
See https://spacy.io/usage/models for available models.
QUESTION
I'm trying to use the spacy_langdetect package and the only example code I can find is (https://spacy.io/universe/project/spacy-langdetect):
...ANSWER
Answered 2021-Mar-20 at 23:11With spaCy v3.0 for components not built-in such as LanguageDetector, you will have to wrap it into a function prior to adding it to the nlp pipe. In your example, you can do the following:
QUESTION
I have weather alert data like
...ANSWER
Answered 2021-Feb-08 at 09:24You just need to iterate over the dictionary key alerts and add key, value to every item(which is a dictionary).
QUESTION
Given this dataframe (which is a subset of mine):
username user_message Polop I love this picture, which is very beautiful Artil Meh Artingo Es un cuadro preciosa, me recuerda a mi infancia. Zona I like it Soi Yuck, to say I hate it would be a euphemism Iyu NaNWhat I'm trying to do is drop rows for which a number of words (tokens) is less than 5 words, and that are not written in English. I'm not familiar with pandas, so I imagined a not so pretty solution:
...ANSWER
Answered 2021-Jan-23 at 22:43Use:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install langdetect
You can use langdetect like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the langdetect component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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