| |
| |
| |
| |
|
|
| from typing import List, Union |
|
|
| _tagger = None |
| _tagger_name = "" |
|
|
|
|
| def dependency_parsing( |
| text: str, |
| model: Union[str, None] = None, |
| tag: str = "str", |
| engine: str = "esupar", |
| ) -> Union[List[List[str]], str]: |
| """ |
| Dependency Parsing |
| |
| :param str text: text to apply dependency parsing to |
| :param str model: model for using with engine \ |
| (for esupar and transformers_ud) |
| :param str tag: output type (str or list) |
| :param str engine: the name of dependency parser |
| :return: str (conllu) or List |
| :rtype: Union[List[List[str]], str] |
| |
| **Options for engine** |
| * *esupar* (default) - Tokenizer, POS tagger and Dependency parser \ |
| using BERT/RoBERTa/DeBERTa models. `GitHub \ |
| <https://github.com/KoichiYasuoka/esupar>`_ |
| * *spacy_thai* - Tokenizer, POS tagger, and dependency parser \ |
| for the Thai language, using Universal Dependencies. \ |
| `GitHub <https://github.com/KoichiYasuoka/spacy-thai>`_ |
| * *transformers_ud* - TransformersUD \ |
| `GitHub <https://github.com/KoichiYasuoka/>`_ |
| * *ud_goeswith* - POS tagging and dependency parsing \ |
| using `goeswith` for subwords |
| |
| **Options for model (esupar engine)** |
| * *th* (default) - KoichiYasuoka/roberta-base-thai-spm-upos model \ |
| `Huggingface \ |
| <https://huggingface.co/KoichiYasuoka/roberta-base-thai-spm-upos>`_ |
| * *KoichiYasuoka/deberta-base-thai-upos* - DeBERTa(V2) model \ |
| pre-trained on Thai Wikipedia texts for POS tagging and \ |
| dependency parsing `Huggingface \ |
| <https://huggingface.co/KoichiYasuoka/deberta-base-thai-upos>`_ |
| * *KoichiYasuoka/roberta-base-thai-syllable-upos* - RoBERTa model \ |
| pre-trained on Thai Wikipedia texts for POS tagging and \ |
| dependency parsing. (syllable level) `Huggingface \ |
| <https://huggingface.co/KoichiYasuoka/roberta-base-thai-syllable-upos>`_ |
| * *KoichiYasuoka/roberta-base-thai-char-upos* - RoBERTa model \ |
| pre-trained on Thai Wikipedia texts for POS tagging \ |
| and dependency parsing. (char level) `Huggingface \ |
| <https://huggingface.co/KoichiYasuoka/roberta-base-thai-char-upos>`_ |
| |
| If you want to train models for esupar, you can read \ |
| `Huggingface <https://github.com/KoichiYasuoka/esupar>`_ |
| |
| **Options for model (transformers_ud engine)** |
| * *KoichiYasuoka/deberta-base-thai-ud-head* (default) - \ |
| DeBERTa(V2) model pretrained on Thai Wikipedia texts \ |
| for dependency parsing (head-detection using Universal \ |
| Dependencies) and question-answering, derived from \ |
| deberta-base-thai. \ |
| trained by th_blackboard.conll. `Huggingface \ |
| <https://huggingface.co/KoichiYasuoka/deberta-base-thai-ud-head>`_ |
| * *KoichiYasuoka/roberta-base-thai-spm-ud-head* - \ |
| roberta model pretrained on Thai Wikipedia texts \ |
| for dependency parsing. `Huggingface \ |
| <https://huggingface.co/KoichiYasuoka/roberta-base-thai-spm-ud-head>`_ |
| |
| **Options for model (ud_goeswith engine)** |
| * *KoichiYasuoka/deberta-base-thai-ud-goeswith* (default) - \ |
| This is a DeBERTa(V2) model pre-trained on Thai Wikipedia \ |
| texts for POS tagging and dependency parsing (using goeswith for subwords) \ |
| `Huggingface <https://huggingface.co/KoichiYasuoka/deberta-base-thai-ud-goeswith>`_ |
| |
| :Example: |
| :: |
| |
| from pythainlp.parse import dependency_parsing |
| |
| print(dependency_parsing("ผมเป็นคนดี", engine="esupar")) |
| # output: |
| # 1 ผม _ PRON _ _ 3 nsubj _ SpaceAfter=No |
| # 2 เป็น _ VERB _ _ 3 cop _ SpaceAfter=No |
| # 3 คน _ NOUN _ _ 0 root _ SpaceAfter=No |
| # 4 ดี _ VERB _ _ 3 acl _ SpaceAfter=No |
| |
| print(dependency_parsing("ผมเป็นคนดี", engine="spacy_thai")) |
| # output: |
| # 1 ผม PRON PPRS _ 2 nsubj _ SpaceAfter=No |
| # 2 เป็น VERB VSTA _ 0 ROOT _ SpaceAfter=No |
| # 3 คนดี NOUN NCMN _ 2 obj _ SpaceAfter=No |
| """ |
| global _tagger, _tagger_name |
|
|
| if _tagger_name != engine: |
| if engine == "esupar": |
| from pythainlp.parse.esupar_engine import Parse |
|
|
| _tagger = Parse(model=model) |
| elif engine == "transformers_ud": |
| from pythainlp.parse.transformers_ud import Parse |
|
|
| _tagger = Parse(model=model) |
| elif engine == "spacy_thai": |
| from pythainlp.parse.spacy_thai_engine import Parse |
|
|
| _tagger = Parse() |
| elif engine == "ud_goeswith": |
| from pythainlp.parse.ud_goeswith import Parse |
|
|
| _tagger = Parse(model=model) |
| else: |
| raise NotImplementedError("The engine doesn't support.") |
|
|
| _tagger_name = engine |
|
|
| return _tagger(text, tag=tag) |
|
|
