nlp_architect.models.bist_parser.BISTModel

class nlp_architect.models.bist_parser.BISTModel(activation='tanh', lstm_layers=2, lstm_dims=125, pos_dims=25)[source]

BIST parser model class. This class handles training, prediction, loading and saving of a BIST parser model. After the model is initialized, it accepts a CoNLL formatted dataset as input, and learns to output dependencies for new input.

Parameters:
  • activation (str, optional) – Activation function to use.
  • lstm_layers (int, optional) – Number of LSTM layers to use.
  • lstm_dims (int, optional) – Number of LSTM dimensions to use.
  • pos_dims (int, optional) – Number of part-of-speech embedding dimensions to use.
model

The underlying LSTM model.

Type:MSTParserLSTM
params

Additional parameters and resources for the model.

Type:tuple
options

User model options.

Type:dict
__init__(activation='tanh', lstm_layers=2, lstm_dims=125, pos_dims=25)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([activation, lstm_layers, …]) Initialize self.
fit(dataset[, epochs, dev]) Trains a BIST model on an annotated dataset in CoNLL file format.
load(path) Loads and initializes a BIST model from file.
predict(dataset[, evaluate]) Runs inference with the BIST model on a dataset in CoNLL file format.
predict_conll(dataset) Runs inference with the BIST model on a dataset in CoNLL object format.
save(path) Saves the BIST model to file.
fit(dataset, epochs=10, dev=None)[source]

Trains a BIST model on an annotated dataset in CoNLL file format.

Parameters:
  • dataset (str) – Path to input dataset for training, formatted in CoNLL/U format.
  • epochs (int, optional) – Number of learning iterations.
  • dev (str, optional) – Path to development dataset for conducting evaluations.
load(path)[source]

Loads and initializes a BIST model from file.

predict(dataset, evaluate=False)[source]

Runs inference with the BIST model on a dataset in CoNLL file format.

Parameters:
  • dataset (str) – Path to input CoNLL file.
  • evaluate (bool, optional) – Write prediction and evaluation files to dataset’s folder.
Returns:

The list of input sentences with predicted dependencies attached.

Return type:

res (list of list of ConllEntry)

predict_conll(dataset)[source]

Runs inference with the BIST model on a dataset in CoNLL object format.

Parameters:dataset (list of list of ConllEntry) – Input in the form of ConllEntry objects.
Returns:The list of input sentences with predicted dependencies attached.
Return type:res (list of list of ConllEntry)
save(path)[source]

Saves the BIST model to file.