Multi-Task Learning
This example is inspired by the classic paper Natural Language Processing (Almost) from Scratch by Collobert et al..
| sentence | chunks | part_of_speech | named_entities | 
|---|---|---|---|
| San Francisco is very foggy | B-NP I-NP B-VP B-ADJP I-ADJP | NNP NNP VBZ RB JJ | B-Loc I-Loc O O O | 
| My dog likes eating sausage | B-NP I-NP B-VP B-VP B-NP | PRP NN VBZ VBG NN | O O O O O | 
| Brutus Killed Julius Caesar | B-NP B-VP B-NP I-NP | NNP VBD NNP NNP | B-Per O B-Per I-Per | 
ludwig experiment \
--dataset nl_data.csv \
  --config config.yaml
With config.yaml:
input_features:
    -
        name: sentence
        type: sequence
        encoder: 
            type: rnn
            cell: lstm
            bidirectional: true
            reduce_output: null
output_features:
    -
        name: chunks
        type: sequence
        decoder: 
            type: tagger
    -
        name: part_of_speech
        type: sequence
        decoder: 
            type: tagger
    -
        name: named_entities
        type: sequence
        decoder: 
            type: tagger