* updating rules and vocabulary for French lemmatization of verbs
* updating the file with French auxiliary verb
* updating rules and vocabulary for French lemmatization of verbs
* adding contributor agreement for amperinet
* adding rules for words with inclusive parentheses wrongly tokenized
* Updated wordforms for Norwegian lemmatizer
Upload of updated lists of wordforms for the Norwegian lemmatizer (nouns, verbs, adverbs, adjectives and lookup).
* Add spaCy contributor agreement for user beatesi
* Updated wordforms for Norwegian lemmatizer
* additional unit test for new entr word not in other lists
* bugfix - unit test works
* use _latin_lower instead of alpha_lower for french
* revert back to ALPHA_LOWER (following the code for languages)
* contributor agreement
<!--- Provide a general summary of your changes in the title. -->
## Description
<!--- Use this section to describe your changes. If your changes required
testing, include information about the testing environment and the tests you
ran. If your test fixes a bug reported in an issue, don't forget to include the
issue number. If your PR is still a work in progress, that's totally fine – just
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Add a rule-based French Lemmatizer following the english one and the excellent PR for [greek language optimizations](https://github.com/explosion/spaCy/pull/2558) to adapt the Lemmatizer class.
### Types of change
<!-- What type of change does your PR cover? Is it a bug fix, an enhancement
or new feature, or a change to the documentation? -->
- Lemma dictionary used can be found [here](http://infolingu.univ-mlv.fr/DonneesLinguistiques/Dictionnaires/telechargement.html), I used the XML version.
- Add several files containing exhaustive list of words for each part of speech
- Add some lemma rules
- Add POS that are not checked in the standard Lemmatizer, i.e PRON, DET, ADV and AUX
- Modify the Lemmatizer class to check in lookup table as a last resort if POS not mentionned
- Modify the lemmatize function to check in lookup table as a last resort
- Init files are updated so the model can support all the functionalities mentioned above
- Add words to tokenizer_exceptions_list.py in respect to regex used in tokenizer_exceptions.py
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [X] I have submitted the spaCy Contributor Agreement.
- [X] I ran the tests, and all new and existing tests passed.
- [X] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Correct some grammatical inaccuracies in lang\ru\examples.py; filled Contributor Agreement
* Correct some grammatical inaccuracies in lang\ru\examples.py
* Move contributor agreement to separate file
* Add words to portuguese language _num_words
* Add words to portuguese language _num_words
* Portuguese - Add/remove stopwords, fix tokenizer, add currency symbols
* Extended punctuation and norm_exceptions in the Portuguese language
* adding e-KTP in tokenizer exceptions list
* add exception token
* removing lines with containing space as it won't matter since we use .split() method in the end, added new tokens in exception
* add tokenizer exceptions list
* combining base_norms with norm_exceptions
* adding norm_exception
* fix double key in lemmatizer
* remove unused import on punctuation.py
* reformat stop_words to reduce number of lines, improve readibility
* updating tokenizer exception
* implement is_currency for lang/id
* adding orth_first_upper in tokenizer_exceptions
* update the norm_exception list
* remove bunch of abbreviations
* adding contributors file
I have added numbers in hindi lex_attrs.py file according to Indian numbering system(https://en.wikipedia.org/wiki/Indian_numbering_system) and here are there english translations:
'शून्य' => zero
'एक' => one
'दो' => two
'तीन' => three
'चार' => four
'पांच' => five
'छह' => six
'सात'=>seven
'आठ' => eight
'नौ' => nine
'दस' => ten
'ग्यारह' => eleven
'बारह' => twelve
'तेरह' => thirteen
'चौदह' => fourteen
'पंद्रह' => fifteen
'सोलह'=> sixteen
'सत्रह' => seventeen
'अठारह' => eighteen
'उन्नीस' => nineteen
'बीस' => twenty
'तीस' => thirty
'चालीस' => forty
'पचास' => fifty
'साठ' => sixty
'सत्तर' => seventy
'अस्सी' => eighty
'नब्बे' => ninety
'सौ' => hundred
'हज़ार' => thousand
'लाख' => hundred thousand
'करोड़' => ten million
'अरब' => billion
'खरब' => hundred billion
<!--- Provide a general summary of your changes in the title. -->
## Description
<!--- Use this section to describe your changes. If your changes required
testing, include information about the testing environment and the tests you
ran. If your test fixes a bug reported in an issue, don't forget to include the
issue number. If your PR is still a work in progress, that's totally fine – just
include a note to let us know. -->
### Types of change
<!-- What type of change does your PR cover? Is it a bug fix, an enhancement
or new feature, or a change to the documentation? -->
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Exceptions for single letter words ending sentence
Sentences ending in "i." (as in "... peka i."), "m." (as in "...än 2000 m."), should be tokenized as two separate tokens.
* Add test
This jargon is not offencive but emotionally colored as funny due to its deviation from the norm for various reasons: immitating a dialect, deliberately wrong spelling emphasizing its low colloquial nature, obsolete form, foreign borrowing with native flections, etc.
Dmitry Briukhanov, Linguist & Pythonist
List created by taking the 2000 top words from a Wikipedia dump and
removing everything that wasn't hiragana.
Tried going through kanji words and deciding what to keep but there were
too many obvious non-stopwords (東京 was in the top 500) and many other
words where it wasn't clear if they should be included or not.
<!--- Provide a general summary of your changes in the title. -->
## Description
This PR corrects the German lemma form for the word "Rang". Initially, the lemma form was "ringen", which is not correct, because it refers to the verb ("ringen") and not to the noun ("Rang").
### Types of change
The lemma form for "Rang" is corrected to "Rang", see also the [Duden](https://www.duden.de/rechtschreibung/Rang) entry.
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Add Romanian lemmatizer lookup table.
Adapted from http://www.lexiconista.com/datasets/lemmatization/
by replacing cedillas with commas (ș and ț).
The original dataset is licensed under the Open Database License.
* Fix one blatant issue in the Romanian lemmatizer
* Romanian examples file
* Add ro_tokenizer in conftest
* Add Romanian lemmatizer test
