Joseph Chee Chang: Difference between revisions

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Demo of the Threddy paper (attached):
Demo of the Threddy paper (attached):
|Organizer Topics=Discovery, Machine Learning, NLP, HCI
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Revision as of 06:06, 21 October 2022



Joseph Chee Chang
Timezone America/Los Angeles (GMT−08:00/GMT−07:00)
Institutional Affiliation(s) Allen Institute
Relevant Projects Semantic Scholar


Group(s) Interfaces, Table 4







Discord

sneakers-the-rat#discourse-modeling22-11-12 19:32:48

Page Schemas#Creating a new Schema Page schemas is mostly a handy way to generate boilerplate templates and link them to semantic properties. A Form (using Page Forms is something that is an interface for filling in values for a template.

For an example of how this shakes out, see Category:Participant Template:Participant Form:Participant

  • go to a `Category:CategoryName` page, creating it if it doesn't already exist.
  • Click "Create schema" in top right
  • If you want a form, check the "Form" box. it is possible to make a schema without a form. The schema just defines what pages will be generated, and the generated pages can be further edited afterwards (note that this might make them inconsistent with the schema)
  • Click "add template" If you are only planning on having one template per category, name the template the same thing as the category.
  • Add fields! Each field can have a corresponding form input (with a type, eg. a textbox, token input, date selector, etc.) and a semantic property.
  • Once you're finished, save the schema
  • Click "Generate pages" on the category page. Typically you want to uncheck any pages that are already bluelinks so you don't overwrite them. You might have to do the 'generate pages' step a few times, and it can take a few minutes, bc it's pretty buggy.


Workshop Submission

What's your interest in this workshop?

With what "frame" do you approach the workshop? (or identity)?

Tool-builder

What materials can you contribute to the workshop for consideration?

Semantic Scholar Resources: https://www.semanticscholar.org/product/api https://allenai.org/data/s2orc

Demo of the Threddy paper (attached):

Organizer-estimated Topics

Discovery, Machine Learning, NLP, HCI