#!/usr/bin/env python3
# -*- coding:utf-8 -*-
"""
This module provides containers for NER sentences.
"""
__author__ = 'Mu Yang <http://muyang.pro>'
__copyright__ = '2018-2023 CKIP Lab'
__license__ = 'GPL-3.0'
from typing import (
NamedTuple as _NamedTuple,
Tuple as _Tuple,
)
from .base import (
BaseTuple as _BaseTuple,
BaseList as _BaseList,
BaseSentence as _BaseSentence,
)
################################################################################################################################
class _NerToken(_NamedTuple):
word: str
ner: str
idx: _Tuple[int, int]
[docs]class NerToken(_BaseTuple, _NerToken):
"""A named-entity recognition token.
Attributes
----------
word : str
the token word.
ner : str
the NER-tag.
idx : Tuple[int, int]
the starting / ending index.
Note
----
This class is an subclass of :class:`tuple`. To change the attribute, please create a new instance instead.
.. admonition:: Data Structure Examples
Text format
Not implemented
List format
Used for :meth:`from_list` and :meth:`to_list`.
.. code-block:: python
[
'中文字' # token word
'LANGUAGE', # NER-tag
(0, 3), # starting / ending index.
]
Dict format
Used for :meth:`from_dict` and :meth:`to_dict`.
.. code-block:: python
{
'word': '中文字', # token word
'ner': 'LANGUAGE', # NER-tag
'idx': (0, 3), # starting / ending index.
}
CkipTagger format
Used for :meth:`from_tagger` and :meth:`to_tagger`.
.. code-block:: python
(
0, # starting index
3, # ending index
'LANGUAGE', # NER-tag
'中文字', # token word
)
"""
def __new__(cls, word, ner, idx, **kwargs): # pylint: disable=signature-differs
return super().__new__(cls, word, ner, tuple(idx), **kwargs)
to_text = NotImplemented
from_text = NotImplemented
########################################################################################################################
[docs] @classmethod
def from_tagger(cls, data):
"""Construct an instance from CkipTagger format."""
idx0, idx1, ner, word = data
return cls(word=word, ner=ner, idx=(idx0, idx1,)) # pylint: disable=no-value-for-parameter
[docs] def to_tagger(self):
"""Transform to CkipTagger format."""
return (*self.idx, self.ner, self.word)
################################################################################################################################
[docs]class NerSentence(_BaseSentence):
"""A named-entity recognition sentence.
.. admonition:: Data Structure Examples
Text format
Not implemented
List format
Used for :meth:`from_list` and :meth:`to_list`.
.. code-block:: python
[
[ '美國', 'GPE', (0, 2), ], # name-entity 1
[ '參議院', 'ORG', (3, 5), ], # name-entity 2
]
Dict format
Used for :meth:`from_dict` and :meth:`to_dict`.
.. code-block:: python
[
{ 'word': '美國', 'ner': 'GPE', 'idx': (0, 2), }, # name-entity 1
{ 'word': '參議院', 'ner': 'ORG', 'idx': (3, 5), }, # name-entity 2
]
CkipTagger format
Used for :meth:`from_tagger` and :meth:`to_tagger`.
.. code-block:: python
[
( 0, 2, 'GPE', '美國', ), # name-entity 1
( 3, 5, 'ORG', '參議院', ), # name-entity 2
]
"""
item_class = NerToken
to_text = NotImplemented
from_text = NotImplemented
########################################################################################################################
[docs] @classmethod
def from_tagger(cls, data):
"""Construct an instance from CkipTagger format."""
return cls(map(cls.item_class.from_tagger, data))
[docs] def to_tagger(self):
"""Transform to CkipTagger format."""
return list(item.to_tagger() for item in self)
################################################################################################################################
[docs]class NerParagraph(_BaseList):
"""A list of named-entity recognition sentence.
.. admonition:: Data Structure Examples
Text format
Not implemented
List format
Used for :meth:`from_list` and :meth:`to_list`.
.. code-block:: python
[
[ # Sentence 1
[ '中文字', 'LANGUAGE', (0, 3), ],
],
[ # Sentence 2
[ '美國', 'GPE', (0, 2), ],
[ '參議院', 'ORG', (3, 5), ],
],
]
Dict format
Used for :meth:`from_dict` and :meth:`to_dict`.
.. code-block:: python
[
[ # Sentence 1
{ 'word': '中文字', 'ner': 'LANGUAGE', 'idx': (0, 3), },
],
[ # Sentence 2
{ 'word': '美國', 'ner': 'GPE', 'idx': (0, 2), },
{ 'word': '參議院', 'ner': 'ORG', 'idx': (3, 5), },
],
]
CkipTagger format
Used for :meth:`from_tagger` and :meth:`to_tagger`.
.. code-block:: python
[
[ # Sentence 1
( 0, 3, 'LANGUAGE', '中文字', ),
],
[ # Sentence 2
( 0, 2, 'GPE', '美國', ),
( 3, 5, 'ORG', '參議院', ),
],
]
"""
item_class = NerSentence
to_text = NotImplemented
from_text = NotImplemented
########################################################################################################################
[docs] @classmethod
def from_tagger(cls, data):
"""Construct an instance from CkipTagger format."""
return cls(map(cls.item_class.from_tagger, data))
[docs] def to_tagger(self):
"""Transform to CkipTagger format."""
return list(item.to_tagger() for item in self)