PublishInCovid19 at WNUT 2020 Shared Task-1: Entity Recognition in Wet Lab Protocols using Structured Learning Ensemble and Contextualised Embeddings

by   Janvijay Singh, et al.

In this paper, we describe the approach that we employed to address the task of Entity Recognition over Wet Lab Protocols – a shared task in EMNLP WNUT-2020 Workshop. Our approach is composed of two phases. In the first phase, we experiment with various contextualised word embeddings (like Flair, BERT-based) and a BiLSTM-CRF model to arrive at the best-performing architecture. In the second phase, we create an ensemble composed of eleven BiLSTM-CRF models. The individual models are trained on random train-validation splits of the complete dataset. Here, we also experiment with different output merging schemes, including Majority Voting and Structured Learning Ensembling (SLE). Our final submission achieved a micro F1-score of 0.8175 and 0.7757 for the partial and exact match of the entity spans, respectively. We were ranked first and second, in terms of partial and exact match, respectively.


page 1

page 2

page 3

page 4


Fancy Man Lauches Zippo at WNUT 2020 Shared Task-1: A Bert Case Model for Wet Lab Entity Extraction

Automatic or semi-automatic conversion of protocols specifying steps in ...

GNTeam at 2018 n2c2: Feature-augmented BiLSTM-CRF for drug-related entity recognition in hospital discharge summaries

Monitoring the administration of drugs and adverse drug reactions are ke...

Detecting Entities in the Astrophysics Literature: A Comparison of Word-based and Span-based Entity Recognition Methods

Information Extraction from scientific literature can be challenging due...

Domain specific BERT representation for Named Entity Recognition of lab protocol

Supervised models trained to predict properties from representations hav...

Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition

We propose an LSTM-based model with hierarchical architecture on named e...

Using Transformer based Ensemble Learning to classify Scientific Articles

Many time reviewers fail to appreciate novel ideas of a researcher and p...

Please sign up or login with your details

Forgot password? Click here to reset