SRL experiments with the BERT-based model

We will run our SRL experiments using the method described in the Setting up the BERT SRL environment section of this chapter. We will begin with basic samples with various sentence structures. We will then challenge the BERT-based model with some more difficult samples to explore the system’s capacity and limits.

Open SRL.ipynb and run the installation cell:

!pip install allennlp==2.1.0 allennlp-models==2.1.0

Then we import the tagging module and a trained BERT predictor:

from allennlp.predictors.predictor import Predictor
import allennlp_models.tagging
import json
predictor = Predictor.from_path("https://storage.googleapis.com/allennlp-public-models/structured-prediction-srl-bert.2020.12.15.tar.gz")

We also add two functions to display the JSON object SRL BERT returns. The first one displays the verb of the predicate and the description:

def head(prediction):
  # Iterating through the json to display...