Best way to correct dependency parsing mistakes

[jama1017]

Hi,

I am using SpaCy's built-in en_core_web_trf to parse out texts that describe a motion instruction, for example "Move the black rock upward by 50 miles" and "Move the black rock north by 50 miles"

In the first example, spaCy would correctly label the preposition "by" as "prep" depending on the verb "Move". However, in the second example, since "upward" has been changed to the noun "north", spaCy would label "by" as "prep" depending on the noun "north", instead of "move" like it previously did.

There are many other examples like this in my data, and I wonder how I can correct these parsing mistakes. Is it through training from scratch, or fine-tuning, or pseudo rehearsal? I tried to search for tutorials on how to fine-tune the DependencyParser but didn't find any up-to-date ones. Any ideas and pointers would be helpful. Thanks so much!

[jama1017]

Just to add onto this - I wonder if it's possible to train a dependency parser from scratch with OntoNotes 5.0 (I believe this is what the out of the box en_core_web_trf was being trained on) but also with some custom data? Would love some guidance on this if people have done this before!!