DeepAI
Log In Sign Up

Extraction of Medication Names from Twitter Using Augmentation and an Ensemble of Language Models

11/12/2021
by   Igor Kulev, et al.
0

The BioCreative VII Track 3 challenge focused on the identification of medication names in Twitter user timelines. For our submission to this challenge, we expanded the available training data by using several data augmentation techniques. The augmented data was then used to fine-tune an ensemble of language models that had been pre-trained on general-domain Twitter content. The proposed approach outperformed the prior state-of-the-art algorithm Kusuri and ranked high in the competition for our selected objective function, overlapping F1 score.

READ FULL TEXT

page 1

page 2

page 3

page 4

06/07/2021

CAiRE in DialDoc21: Data Augmentation for Information-Seeking Dialogue System

Information-seeking dialogue systems, including knowledge identification...
08/10/2017

Location Name Extraction from Targeted Text Streams using Gazetteer-based Statistical Language Models

Extracting location names from informal and unstructured texts requires ...
04/01/2020

Deep Entity Matching with Pre-Trained Language Models

We present Ditto, a novel entity matching system based on pre-trained Tr...
07/24/2020

Named entity recognition in chemical patents using ensemble of contextual language models

Chemical patent documents describe a broad range of applications holding...
05/06/2019

Anonymized BERT: An Augmentation Approach to the Gendered Pronoun Resolution Challenge

We present our 7th place solution to the Gendered Pronoun Resolution cha...
09/20/2021

Language Identification with a Reciprocal Rank Classifier

Language identification is a critical component of language processing p...