The md-to-html demo is a good one, but worth mentioning that the Markdown parser[1] being used may not be suitable for more complex documents. From the README:
> "...it is not recommended to use this parser where correctness is important. The main goal for this parser is to provide syntactical information for syntax highlighting..."
There's also a separate block-level and inline parser, not sure how `tbsp` handles nested or multi-stage parsing.
> While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage.
So it can't produce articles that require many edits? Meaning it can produce publication-ready articles that don't need lots of edits? Or it can't produce publication-ready articles, and the articles produced require lots of edits? I can't make sense of this statement.
Very cool work but I'm a bit perplexed by their first example/diagram from the blog post (which is presumably cherry-picked?). The event "The dogs are waiting." overlapping with the event "The dogs are pulling the sled." seems like a poor joint labeling of the events. The two obviously cannot co-occur, and this feels like a pretty easy opportunity for the model to demonstrate its understanding of event disentanglement.
The remaining examples from the paper don't do much in the way of convincing me this is a one-off issue. The recognition of multiple events globally is good, but perhaps extra care should be taken at overlapping event boundaries (e.g. additional local constraints in the loss/regularization scheme that encourage event splitting or time boundaries "snapping-to-grid" if confidence of co-occurrence is low).
> "...it is not recommended to use this parser where correctness is important. The main goal for this parser is to provide syntactical information for syntax highlighting..."
There's also a separate block-level and inline parser, not sure how `tbsp` handles nested or multi-stage parsing.
[1]: https://github.com/tree-sitter-grammars/tree-sitter-markdown