ckipnlp.container.ner module¶
This module provides containers for NER sentences.
- class ckipnlp.container.ner.NerToken(word, ner, idx, **kwargs)[source]¶
Bases:
BaseTuple
,_NerToken
A named-entity recognition token.
- Variables
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
tuple
. To change the attribute, please create a new instance instead.Data Structure Examples
- Text format
Not implemented
- List format
Used for
from_list()
andto_list()
.[ '中文字' # token word 'LANGUAGE', # NER-tag (0, 3), # starting / ending index. ]
- Dict format
Used for
from_dict()
andto_dict()
.{ 'word': '中文字', # token word 'ner': 'LANGUAGE', # NER-tag 'idx': (0, 3), # starting / ending index. }
- CkipTagger format
Used for
from_tagger()
andto_tagger()
.( 0, # starting index 3, # ending index 'LANGUAGE', # NER-tag '中文字', # token word )
- class ckipnlp.container.ner.NerSentence(initlist=None)[source]¶
Bases:
BaseSentence
A named-entity recognition sentence.
Data Structure Examples
- Text format
Not implemented
- List format
Used for
from_list()
andto_list()
.[ [ '美國', 'GPE', (0, 2), ], # name-entity 1 [ '參議院', 'ORG', (3, 5), ], # name-entity 2 ]
- Dict format
Used for
from_dict()
andto_dict()
.[ { '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
from_tagger()
andto_tagger()
.[ ( 0, 2, 'GPE', '美國', ), # name-entity 1 ( 3, 5, 'ORG', '參議院', ), # name-entity 2 ]
- class ckipnlp.container.ner.NerParagraph(initlist=None)[source]¶
Bases:
BaseList
A list of named-entity recognition sentence.
Data Structure Examples
- Text format
Not implemented
- List format
Used for
from_list()
andto_list()
.[ [ # 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
from_dict()
andto_dict()
.[ [ # 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
from_tagger()
andto_tagger()
.[ [ # Sentence 1 ( 0, 3, 'LANGUAGE', '中文字', ), ], [ # Sentence 2 ( 0, 2, 'GPE', '美國', ), ( 3, 5, 'ORG', '參議院', ), ], ]
- item_class¶
alias of
NerSentence