diff --git a/_images/pp.svg b/_images/pp.svg deleted file mode 100644 index 18a6048..0000000 --- a/_images/pp.svg +++ /dev/null @@ -1,1757 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Mr. Bennet - Mrs. Long - Lydia - Mr. Bingley - Sir William - Charlotte - Elizabeth - Jane - Mrs. Bennet - Kitty - Mary - Mrs. Hurst - Mr. Darcy - Miss Bingley - Bingley - Miss De Bourgh - Colonel Forster - Meryton - Mrs. Philips - Longbourn - Mrs. Gardiner - Mr. Collins - Lady Catherine - Mr. Denny - Mr. Wickham - Mr. - Rosings - Colonel Fitzwilliam - Georgiana - Mrs. Reynolds - - diff --git a/_sources/reference.rst.txt b/_sources/reference.rst.txt index 0e41a32..3efcc2c 100644 --- a/_sources/reference.rst.txt +++ b/_sources/reference.rst.txt @@ -184,10 +184,3 @@ Plot utils .. automodule:: renard.plot_utils :members: - - -NER utils ---------- - -.. automodule:: renard.ner_utils - :members: diff --git a/genindex.html b/genindex.html index 7b22b7c..ee88503 100644 --- a/genindex.html +++ b/genindex.html @@ -98,11 +98,9 @@

Index

_

@@ -315,10 +307,6 @@

C

D

-
  • dynamic_graph_to_gephi_graph() (in module renard.graph_utils)
    • @@ -359,10 +347,6 @@

    G

    H

    - - + - - -
    -
    • renard.pipeline.stanford_corenlp @@ -585,6 +550,8 @@

      R

    • module
    +
    • renard.plot_utils diff --git a/introduction.html b/introduction.html index 87866e1..1574a08 100644 --- a/introduction.html +++ b/introduction.html @@ -91,7 +91,7 @@

      IntroductionLabatutAndBost2019 for a more complete overview of character networks and their automated extraction.

      -_images/pp.svg +pp.svg diff --git a/objects.inv b/objects.inv index 26ef636..66f45e9 100644 Binary files a/objects.inv and b/objects.inv differ diff --git a/py-modindex.html b/py-modindex.html index 8f743d6..7013032 100644 --- a/py-modindex.html +++ b/py-modindex.html @@ -96,11 +96,6 @@

      Python Module Index

    		    renard.graph_utils
        - renard.ner_utils -
        diff --git a/reference.html b/reference.html index d9128f1..08969ea 100644 --- a/reference.html +++ b/reference.html @@ -96,7 +96,6 @@
  • Utils
    • @@ -1138,14 +1137,6 @@

    Coreference Resolution __eq__(other)

    Return self==value.

    -
    -
    Parameters
    -

    other (Mention) –

    -
    -
    Return type
    -

    bool

    -
    -
    @@ -2747,174 +2738,6 @@

    Hypocorism -

    NER utils

    -
    -
    -class renard.ner_utils.DataCollatorForTokenClassificationWithBatchEncoding(tokenizer, pad_to_multiple_of=None)
    -

    Same as transformers.DataCollatorForTokenClassification, -except it correctly returns a BatchEncoding object with -correct encodings attribute.

    -

    Don’t know why this is not the default ?

    -
    -
    Parameters
    -
      -

    • tokenizer (PreTrainedTokenizerFast) –

      • -

    • pad_to_multiple_of (Optional[int]) –

      • -
    -
    -
    -
    -
    -__call__(features)
    -

    Call self as a function.

    -
    -
    Parameters
    -

    features (List[dict]) –

    -
    -
    Return type
    -

    Union[dict, BatchEncoding]

    -
    -
    -
    - -
    -
    -__init__(tokenizer, pad_to_multiple_of=None)
    -
    -
    Parameters
    -
      -

    • tokenizer (PreTrainedTokenizerFast) –

      • -

    • pad_to_multiple_of (Optional[int]) –

      • -
    -
    -
    -
    - -
    - -
    -
    -class renard.ner_utils.NERDataset(elements, tokenizer, context_mask=None)
    -
    -
    Variables
    -

    _context_mask – for each element, a mask indicating which -tokens are part of the context (1 for context, 0 for text on -which to perform inference). The mask allows to discard -predictions made for context at inference time, even though -the context can still be passed as input to the model.

    -
    -
    Parameters
    -
      -

    • elements (List[List[str]]) –

      • -

    • tokenizer (PreTrainedTokenizerFast) –

      • -

    • context_mask (Optional[List[List[int]]]) –

      • -
    -
    -
    -
    -
    -__init__(elements, tokenizer, context_mask=None)
    -
    -
    Parameters
    -
      -

    • elements (List[List[str]]) –

      • -

    • tokenizer (PreTrainedTokenizerFast) –

      • -

    • context_mask (Optional[List[List[int]]]) –

      • -
    -
    -
    -
    - -
    - -
    -
    -renard.ner_utils._tokenize_and_align_labels(examples, tokenizer, label_all_tokens=True)
    -

    Adapted from https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/token_classification.ipynb#scrollTo=vc0BSBLIIrJQ

    -
    -
    Parameters
    -
      -

    • examples – an object with keys ‘tokens’ and ‘labels’

      • -

    • tokenizer (PreTrainedTokenizerFast) –

      • -

    • label_all_tokens (bool) –

      • -
    -
    -
    -
    - -
    -
    -renard.ner_utils.hgdataset_from_conll2002(path, tag_conversion_map=None, separator='\\t', **kwargs)
    -

    Load a CoNLL-2002 file as a Huggingface Dataset.

    -
    -
    Parameters
    -
    -
    -
    Return type
    -

    Dataset

    -
    -
    Returns
    -

    a datasets.Dataset with features ‘tokens’ and ‘labels’.

    -
    -
    -
    - -
    -
    -renard.ner_utils.load_conll2002_bio(path, tag_conversion_map=None, separator='\\t', **kwargs)
    -

    Load a file under CoNLL2022 BIO format. Sentences are expected -to be separated by end of lines. Tags should be in the CoNLL-2002 -format (such as ‘B-PER I-PER’) - If this is not the case, see the -tag_conversion_map argument.

    -
    -
    Parameters
    -
      -

    • path (str) – path to the CoNLL-2002 formatted file

      • -

    • separator (str) – separator between token and BIO tags

      • -

    • tag_conversion_map (Optional[Dict[str, str]]) – conversion map for tags found in the -input file. Example : {'B': 'B-PER', 'I': 'I-PER'}

      • -

    • kwargs – additional kwargs for open (such as -encoding or newline).

      • -
    -
    -
    Return type
    -

    Tuple[List[List[str]], List[str], List[NEREntity]]

    -
    -
    Returns
    -

    (sentences, tokens, entities)

    -
    -
    -
    - -
    -
    -renard.ner_utils.ner_entities(tokens, bio_tags, resolve_inconsistencies=True)
    -

    Extract NER entities from a list of BIO tags

    -
    -
    Parameters
    -
      -

    • tokens (List[str]) – a list of tokens

      • -

    • bio_tags (List[str]) – a list of BIO tags. In particular, BIO tags -should be in the CoNLL-2002 form (such as ‘B-PER I-PER’)

      • -

    • resolve_inconsistencies (bool) –

      • -
    -
    -
    Return type
    -

    List[NEREntity]

    -
    -
    Returns
    -

    A list of ner entities, in apparition order

    -
    -
    -
    - diff --git a/searchindex.js b/searchindex.js index b78d3ca..3fd45ef 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ 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