merge malaya-graph

crnewell · Apr 3, 2023 · 40e4ea4 · 40e4ea4
1 parent 7af8f40
commit 40e4ea4
Show file tree

Hide file tree

Showing 28 changed files with 5,010 additions and 105 deletions.
diff --git a/README-pypi.rst b/README-pypi.rst
@@ -51,9 +51,14 @@ Features
 -  **Spelling Correction**, using local Malaysia NLP researches hybrid with Transformer-Bahasa to auto-correct any malay words and NeuSpell using T5-Bahasa.
 -  **Abstractive Summarization**, provide abstractive summarization using T5-Bahasa.
 -  **Extractive Summarization**, Extractive interface using Transformer-Bahasa and Doc2Vec.
+-  **Text to Knowledge Graph**, Generate knowledge graph from human sentences.
 -  **Topic Modeling**, provide Transformer-Bahasa, LDA2Vec, LDA, NMF, LSA interface and easy BERTopic integration.
 -  **EN-MS Translation**, provide English to standard Malay using T5-Bahasa.
+-  **IND-MS Translation**, provide Indonesian to standard Malay using T5-Bahasa.
+-  **JAV-MS Translation**, provide Javanese to standard Malay using T5-Bahasa.
 -  **MS-EN Translation**, provide standard Malay to English using T5-Bahasa.
+-  **MS-IND Translation**, provide standard Malay to Indonesian using T5-Bahasa.
+-  **MS-JAV Translation**, provide standard Malay to Javanese using T5-Bahasa.
 -  **Zero-shot classification**, provide Zero-shot classification interface using Transformer-Bahasa to recognize texts without any labeled training data.
 -  **Zero-shot Entity Recognition**, provide Zero-shot entity tagging interface using Transformer-Bahasa to extract entities.
 -  **Constituency Parsing**, breaking a text into sub-phrases using finetuned Transformer-Bahasa.  
@@ -62,6 +67,7 @@ Features
 -  **Emotion Analysis**, detect and recognize 6 different emotions of texts using finetuned Transformer-Bahasa.
 -  **Entity Recognition**, seeks to locate and classify named entities mentioned in text using finetuned Transformer-Bahasa.
 -  **Jawi-to-Rumi**, convert from Jawi to Rumi using Transformer.
+-  **Knowledge Graph to Text**, Generate human sentences from a knowledge graph.
 -  **Language Detection**, using Fast-text and Sparse Deep learning Model to classify Malay (formal and social media), Indonesia (formal and social media), Rojak language and Manglish.
 -  **Language Model**, using KenLM, Masked language model using BERT, ALBERT and RoBERTa, and GPT2 to do text scoring.
 -  **NSFW Detection**, detect NSFW text using rules based and subwords Naive Bayes.

diff --git a/README.rst b/README.rst
@@ -70,6 +70,7 @@ Features
 -  **Spelling Correction**, using local Malaysia NLP researches hybrid with Transformer-Bahasa to auto-correct any malay words and NeuSpell using T5-Bahasa.
 -  **Abstractive Summarization**, provide abstractive summarization using T5-Bahasa.
 -  **Extractive Summarization**, Extractive interface using Transformer-Bahasa and Doc2Vec.
+-  **Text to Knowledge Graph**, Generate knowledge graph from human sentences.
 -  **Topic Modeling**, provide Transformer-Bahasa, LDA2Vec, LDA, NMF, LSA interface and easy BERTopic integration.
 -  **EN-MS Translation**, provide English to standard Malay using T5-Bahasa.
 -  **IND-MS Translation**, provide Indonesian to standard Malay using T5-Bahasa.
@@ -85,6 +86,7 @@ Features
 -  **Emotion Analysis**, detect and recognize 6 different emotions of texts using finetuned Transformer-Bahasa.
 -  **Entity Recognition**, seeks to locate and classify named entities mentioned in text using finetuned Transformer-Bahasa.
 -  **Jawi-to-Rumi**, convert from Jawi to Rumi using Transformer.
+-  **Knowledge Graph to Text**, Generate human sentences from a knowledge graph.
 -  **Language Detection**, using Fast-text and Sparse Deep learning Model to classify Malay (formal and social media), Indonesia (formal and social media), Rojak language and Manglish.
 -  **Language Model**, using KenLM, Masked language model using BERT, ALBERT and RoBERTa, and GPT2 to do text scoring.
 -  **NSFW Detection**, detect NSFW text using rules based and subwords Naive Bayes.

diff --git a/docs/Api.rst b/docs/Api.rst
@@ -155,6 +155,18 @@ malaya.summarization.extractive
 .. automodule:: malaya.summarization.extractive
     :members:
 
+malaya.text_to_kg.e2e
+---------------------------------
+
+.. automodule:: malaya.text_to_kg.e2e
+    :members:
+
+malaya.text_to_kg.parser
+---------------------------------
+
+.. automodule:: malaya.text_to_kg.parser
+    :members:
+
 malaya.topic_model.decomposition
 ---------------------------------
 
@@ -245,6 +257,13 @@ malaya.jawi_rumi
 .. automodule:: malaya.jawi_rumi
     :members:
 
+malaya.kg_to_text
+-------------------------
+
+.. automodule:: malaya.kg_to_text
+    :members:
+
+
 malaya.language_detection
 -------------------------
 

diff --git a/docs/README.rst b/docs/README.rst
@@ -70,6 +70,7 @@ Features
 -  **Spelling Correction**, using local Malaysia NLP researches hybrid with Transformer-Bahasa to auto-correct any malay words and NeuSpell using T5-Bahasa.
 -  **Abstractive Summarization**, provide abstractive summarization using T5-Bahasa.
 -  **Extractive Summarization**, Extractive interface using Transformer-Bahasa and Doc2Vec.
+-  **Text to Knowledge Graph**, Generate knowledge graph from human sentences.
 -  **Topic Modeling**, provide Transformer-Bahasa, LDA2Vec, LDA, NMF, LSA interface and easy BERTopic integration.
 -  **EN-MS Translation**, provide English to standard Malay using T5-Bahasa.
 -  **IND-MS Translation**, provide Indonesian to standard Malay using T5-Bahasa.
@@ -85,6 +86,7 @@ Features
 -  **Emotion Analysis**, detect and recognize 6 different emotions of texts using finetuned Transformer-Bahasa.
 -  **Entity Recognition**, seeks to locate and classify named entities mentioned in text using finetuned Transformer-Bahasa.
 -  **Jawi-to-Rumi**, convert from Jawi to Rumi using Transformer.
+-  **Knowledge Graph to Text**, Generate human sentences from a knowledge graph.
 -  **Language Detection**, using Fast-text and Sparse Deep learning Model to classify Malay (formal and social media), Indonesia (formal and social media), Rojak language and Manglish.
 -  **Language Model**, using KenLM, Masked language model using BERT, ALBERT and RoBERTa, and GPT2 to do text scoring.
 -  **NSFW Detection**, detect NSFW text using rules based and subwords Naive Bayes.