Synonyms | Chinese synonyms : Chatbot , Intelligent Q | Natural Language Processing library
kandi X-RAY | Synonyms Summary
kandi X-RAY | Synonyms Summary
:herb: Chinese synonyms: Chatbot, Intelligent Q&A Toolkit
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Top functions reviewed by kandi - BETA
- Compares two strings
- Segment words and tags
- Compute similarity between two strings
- Get word vectors from a sentence
- Download a file
- Fix file name
- Print progress bar
- Get the width of the console
- Test the word vector
- Return the vector of a word
- Display a progress bar
- Return a string representation of a thermometer
- Test the similarity between two sentences
- Compute the similarity between two strings
- Test the similarity
- Computes the Levenshtein distance between two sentences
- Check if a string is a ZHSM string
- Compare two synonyms
- Returns a string representation of a sentence
- Return a dictionary containing the memory information
- Returns test results
- Load a word2vec model
- Test parse extract tags
- Display a word
- Load word2vec data
- Load stopwords from file
- Tokenize a docstring
Synonyms Key Features
Synonyms Examples and Code Snippets
Lines of Code : 18License : Permissive (MIT)
Copy%good
~exclamation this is ~so ~good
~exclamation
wow
omg
~so
so
very
extremely
~good
good
great
wonderful
> wow this is extremely great
( %good )
from wordhoard import synonyms
list_of_words = ['mother', 'daughter', 'father', 'son']
synonyms_results = {}
for word in list_of_words:
results = synonyms.query_synonym_com(word)
synonyms_results[word] = results
for key, value in synonyms from wordhoard import synonyms
synonym_01 = synonyms.query_collins_dictionary_synonym('mother')
synonym_02 = synonyms.query_synonym_com('mother')
synonym_03 = synonyms.query_thesaurus_com('mother')
synonym_04 = synonyms.query_thesaurus_plus('mother' 
License : No LicenseCopypublic static void mergeClasses(HashMap groups, String[][] synonyms) {
for (String[] entry : synonyms) {
String name1 = entry[0];
String name2 = entry[1];
NameSet set1 = groups.get(name1);
NameSet set2 = groups.get(name2);
public static void connectEdges(Graph graph, String[][] synonyms) {
for (String[] entry : synonyms) {
String name1 = entry[0];
String name2 = entry[1];
graph.addEdge(name1, name2);
}
} @JsonProperty("synonyms")
public void setSynonyms(List synonyms) {
this.synonyms = synonyms;
} for word_data in json_response:
for meaning_data in word_data['meanings']:
print(meaning_data['partOfSpeech'])
for definition in meaning_data['definitions']:
print(definition['definition'])
verbs = ['be','have', 'find', 'use', 'show', 'increase', 'detect', 'do', 'determine', 'demonstrate', 'observe','suggest']
for i, verb in enumerate(verbs):
for j in range(i + 1, len(verbs)):
v1 = wordnet.synset(verbs[i]+ '.v.01>>> import decimal
>>> decimal.getcontext().rounding
'ROUND_HALF_EVEN'
>>> decimal.getcontext().rounding = decimal.ROUND_HALF_DOWN
>>> (decimal.Decimal(3) + decimal.Decimal(4)) / 2
Decimal('3')
>>&dct = {'Desserts': ['afters', 'sweet', 'dessert'}}
df['synonyms'] = df['primary_cuisine'].map(dct)
Community Discussions
Trending Discussions on Synonyms
QUESTION
My goal is to return the same results when searching by the symbol or html encoded version.
Example Queries:
ANSWER
Answered 2022-Mar-26 at 06:47What you are looking for is the html strip char filter, which works not only for two symbols but for a broad html characters.
Working example
Index mapping with html strip char filter
QUESTION
After I added synonym analyzer to my_index, the index became case-sensitive
I have one property called nationality that has synonym analyzer. But it seems that this property become case sensitive because of the synonym analyzer.
Here is my /my_index/_mappings
ANSWER
Answered 2022-Mar-22 at 21:14Did you apply synonym filter after adding your data into index?
If so, probably "India COUNTRY" phrase was indexed exactly as "India COUNTRY". When you sent a match query to index, your query was analyzed and sent as "INDIA COUNTRY" because you have uppercase filter anymore, it is matched because you are using match query, it is enough to match one of the words. "COUNTRY" word provide this.
But, when you sent one word query "india" then it is analyzed and converted to "INDIA" because of your uppercase filter but you do not have any matching word on your index. You just have a document contains "India COUNTRY".
My answer has a little bit assumption. I hope that it will be useful to understand your problem.
QUESTION
I have just subbed to wordsAPI https://www.wordsapi.com/
and pasted the code to fetch data straight from their Docs:
...ANSWER
Answered 2022-Mar-12 at 04:43You should use res.json() to fetch data:
QUESTION
I've been trying to figure this one out for hours, to no avail.
...ANSWER
Answered 2022-Mar-09 at 11:56Use a for loop with good variable names so it's easy to keep track of what you are currently iterating over:
QUESTION
I'm pulling my hairs here. I have a Google Assistant application that I build with Jovo 4 and Google Actions Builder.
The goal is to create a HelpScene, which shows some options that explain the possibilities/features of the app on selection. This is the response I return from my Webhook. (This is Jovo code, but doesn't matter as this returns a JSON when the Assistant calls the webhook.)
...ANSWER
Answered 2022-Feb-23 at 15:32Okay, after days of searching, I finally figured it out.
It did have something to do with the Jovo framework/setup and/or the scene parameter in the native response.
This is my component, in which I redirect new users to the HelpScene. This scene should show multiple cards in a list/collection/whatever on which the user can tap to receive more information about the application's features.
QUESTION
I have a long list of words :
...ANSWER
Answered 2022-Feb-10 at 10:23Regarding the updated question, this solution works on my machine.
QUESTION
In torch.nn.functional.interpolate what's the difference between the modes linear and bilinear?
To me, these are usually synonyms with regards to image resizing...
...ANSWER
Answered 2022-Feb-04 at 16:48Pytorch is explicitly differentiating between 1d interpolation (linear) and 2d interpolation (bilinear).
They differ in the the dimensionality of the input argument they are allowed to work on ( see here ). Specifically, linear works on 3D inputs and bilinear works on 4D inputs because the first two dimensions (mini-batch x channels) are understood not to be interpolated.
QUESTION
I have a corpus of synonyms and non-synonyms. These are stored in a list of python dictionaries like {"sentence1": , "sentence2": , "label": <1.0 or 0.0> }. Note that this words (or sentences) do not have to be a single token in the tokenizer.
I want to fine-tune a BERT-based model to take both sentences like: [[CLS], ], ...,, [SEP], ], ..., , [SEP]] and predict the "label" (a measurement between 0.0 and 1.0).
What is the best approach to organized this data to facilitate the fine-tuning of the huggingface transformer?
...ANSWER
Answered 2022-Feb-02 at 14:58You can use the Tokenizer __call__ method to join both sentences when encoding them.
In case you're using the PyTorch implementation, here is an example:
QUESTION
When i'm searching for t-shirts on my solr, it returns shirts first. I configured my field as follows:
...ANSWER
Answered 2022-Jan-23 at 14:56Here you are using the StandardTokenizerFactory for your field which is creating a token as shirt and hence a match.
StandardTokenizerFactory :-
It tokenizes on whitespace, as well as strips characters
The Documentation for StandardTokenizerFactory mentions as :-
Splits words at punctuation characters, removing punctuations. However, a dot that's not followed by whitespace is considered part of a token. Splits words at hyphens, unless there's a number in the token. In that case, the whole token is interpreted as a product number and is not split. Recognizes email addresses and Internet hostnames as one token.
If you want to perform search on the "t-shirt", then it should be tokenized.
I would suggest you to use the KeywordTokenizerFactory
Keyword Tokenizer does not split the input provided to it. It does not do any processing on the string, and the entire string is treated as a single token. This doesn't actually do any tokenization. It returns the original text as one term.
This KeywordTokenizerFactory is used for sorting or faceting requirements, where one want to perform the exact match. Its helpful in faceting and sorting.
You can have another field and apply KeywordTokenizerFactory to it and perform your search on it.
QUESTION
Using .net 6 minimal API, what' the best way to programmatically get the wwwroot URL?
So that I can transform a path like: wwwroot/audio/recording1.mp3 into a string like http://localhost:5000/audio/recording1.mp3 then return as json so that a user can access?
ANSWER
Answered 2022-Jan-13 at 12:52You can try building the url yourself from HttpContext.Request:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install Synonyms
You can use Synonyms like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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