Reader small image

You're reading from  Transformers for Natural Language Processing - Second Edition

Product typeBook
Published inMar 2022
PublisherPackt
ISBN-139781803247335
Edition2nd Edition
Right arrow
Author (1)
Denis Rothman
Denis Rothman
author image
Denis Rothman

Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive Natural Language Processing (NLP) chatbots applied as an automated language teacher for Moet et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an Advanced Planning and Scheduling (APS) solution used worldwide.
Read more about Denis Rothman

Right arrow

Difficult samples

This section will run samples that contain problems that the BERT-based transformer will first solve. Finally, we will end with an intractable sample.

Let’s start with a complex sample that the BERT-based transformer can analyze.

Sample 4

Sample 4 takes us into more tricky SRL territory. The sample separates Alice from the verb liked, creating a long-term dependency that has to jump over whose husband went jogging every Sunday.

The sentence is:

Alice, whose husband went jogging every Sunday, liked to go to a dancing class in the meantime.

A human can isolate Alice and find the predicate:

Alice liked to go to a dancing class in the meantime.

Can the BERT model find the predicate like us?

Let’s find out by first running the code in SRL.ipynb:

prediction=predictor.predict(
    sentence="Alice, whose husband went jogging every Sunday, liked to go to a dancing class in the meantime."
)
head(prediction)
...
lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Transformers for Natural Language Processing - Second Edition
Published in: Mar 2022Publisher: PacktISBN-13: 9781803247335

Author (1)

author image
Denis Rothman

Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive Natural Language Processing (NLP) chatbots applied as an automated language teacher for Moet et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an Advanced Planning and Scheduling (APS) solution used worldwide.
Read more about Denis Rothman