How joydeb28/nlp works
This repository is a collection of independent NLP examples, not one integrated application. Its workflows span intent classification, entity and linguistic analysis, and text classification or similarity; shared services and a common entry point are not evident. The graph shows the sampled implementations and major task areas indicated by the tree. Several modules are unsampled, so their internal wiring is omitted.
Main entry points: nn.py BiLSTM-CNN NER · intent_find_main.py RNN intent · intent_find_new.py CNN intent · movie_review_with_RNN.py Movie-review RNN
Components 24
Intent Models
- RNN intent
Intent_Identificatin_RNN/intent_find_main.py - RNN preprocessing
Intent_Identificatin_RNN/preprocessor.py - CNN intent
Intent_identification_CNN/intent_find_new.py - CNN preprocessing
Intent_identification_CNN/preprocessor.py - Intent examples
Intent_Identificatin_RNN/data/intent_classes
Entity Analysis
- BiLSTM-CNN NER
Named_Entity-Recognition_Bidirectional_LSTM_CNN/nn.py - NER preprocessing
Named_Entity-Recognition_Bidirectional_LSTM_CNN/prepro.py - NER scoring
Named_Entity-Recognition_Bidirectional_LSTM_CNN/validation.py - spaCy NER
NameEntityRecognition/ner_spacy.py - NLTK NER
NameEntityRecognition/ner_nltk.py - NLTK POS
Part-of-Speech-Tagging/nltk_pos_tagging.py - nlpnet POS
Part-of-Speech-Tagging/nlpnet_pos_tagging.py
Text Classification
- Spam RNN
Spam_Detection/Main.py - Spam corpus
Spam_Detection/spam.csv - Movie-review RNN
Movie Review with RNN/movie_review_with_RNN.py - IMDB loader
Movie Review with RNN/imdb.py - Review sentiment
sentiment_analysis/NN_for_Analysis.py - Yes/no classifier
yes_no_response_classification/response_classifier.py
Language Tools
- Sentence similarity
Semantic_Similarity/Semantic-Similarity-1/align_penalize_any_wordSimilarity.py - Link grammar parser
Link_Grammar_Parser/Dependency-Grammar-NLP-Python.py - ELMo and NNLM
ELMO/embeddings.py - Word embeddings
Word_Embeddings/load_embeddings.py
Other components
- Text user
- Predictions or analysis
Connections 34
- Text user → RNN intent: submits text
- RNN intent → RNN preprocessing: imports preprocessing
- RNN intent → Predictions or analysis: classifies intent
- Text user → CNN intent: submits text
- CNN intent → CNN preprocessing: imports preprocessing
- CNN intent → Predictions or analysis: classifies intent
- Text user → BiLSTM-CNN NER: provides text
- BiLSTM-CNN NER → NER preprocessing: prepares batches
- BiLSTM-CNN NER → NER scoring: scores predictions
- BiLSTM-CNN NER → Predictions or analysis: tags entities
- Text user → spaCy NER: submits text
- spaCy NER → Predictions or analysis: extracts entities
- Text user → NLTK NER: submits text
- NLTK NER → Predictions or analysis: extracts entities
- Text user → NLTK POS: submits text
- NLTK POS → Predictions or analysis: tags parts
- Text user → nlpnet POS: submits text
- nlpnet POS → Predictions or analysis: tags parts
- Spam RNN → Spam corpus: reads corpus
- Spam RNN → Predictions or analysis: predicts spam
- Text user → Movie-review RNN: requests sentiment
- Movie-review RNN → IMDB loader: loads reviews
- Movie-review RNN → Predictions or analysis: predicts sentiment
- Text user → Review sentiment: provides reviews
- Review sentiment → Predictions or analysis: classifies sentiment
- Text user → Yes/no classifier: submits response
- Yes/no classifier → Predictions or analysis: classifies response
- Text user → Sentence similarity: provides sentences
- Sentence similarity → Predictions or analysis: scores similarity
- Text user → Link grammar parser: submits text
- Link grammar parser → Predictions or analysis: parses grammar
- Text user → ELMo and NNLM: provides sentences
- ELMo and NNLM → Predictions or analysis: returns embeddings
- Word embeddings → Predictions or analysis: builds vectors