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User:Jting2/sandbox

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Welcome to the "getting started" page for the LINQS Wikipedia SRL Hackathon! Table of contents comes immediately before the first section.

Rather than editing this page, you should create an account, which I will cover via Zoom. You can then create a user page of any name you like at https://en.wikipedia.org/wiki/User:YOUR_USER_NAME/YOUR_DESIRED_PAGE_NAME. (I would name the page "sandbox" which is the default.)

Once you've done that, come back this page and hit "Edit source" button at the top-right. Once you copy this wiki markup directly to your sandbox page, you can publish it. From there, start making changes to experiment. If you ever need to revert, you can always go to the "View history" tab in the upper right (next to "Edit source") and "undo."

The table of contents always precedes the first section header whenever there are more than four sections or subsection. The remainder of the article just gives an introduction to basic syntax.

Big Section[edit]

This should be our default

Medium Subsection[edit]

Used as subsections.


Small Sub-subsection[edit]

We probably won't need this small of a section today.

Another Subsection[edit]

More text here.

Math[edit]

Here is some inline math, . And here is a displayed equation:


It works just as Latex, except instead of surrounding things with dollar signs, you wrap them in HTML-like mathenvironments.

References[edit]

Hyperlinks[edit]

Links internal to Wikipedia use double brackets. These links will always be inline. The anchor text by default will be the page name; if you want a different anchor text, use the long bar, for example by linking to wiki.

A link to a site outside wikipedia contains the URL in single brackets, like so [1]. This creates a reference at the bottom of the page. If you want to have inline anchor text for the URL, use a space followed by the anchor text: LINQS. Note that anchor text for external links is discouraged outside lists of external links. In general, we probably won't be using these that much.

Citations[edit]

These use the reference template. Mostly, we will be using the Template:Cite_journal and Template:Cite_conference templates. The Wikipedia:Citing_sources article gives an overview of citation styles, but is probably more detailed than what you need for most tasks.

Here is an example of an example of a citation that appears in the Reference list.[1] To make it appear directly, remove the <ref> tags. (To treat a block of text as a string literal rather than Wikipedia code, use the <nowiki> tag.)

Tables[edit]

Example table from the article on relational models.

Customer relation[edit]

Customer ID Tax ID Name Address [More fields…]
1234567890 555-5512222 Ramesh 323 Southern Avenue
2223344556 555-5523232 Adam 1200 Main Street
3334445563 555-5533323 Shweta 871 Rani Jhansi Road
4232342432 555-5325523 Sarfaraz 123 Maulana Azad Sarani

Multi-Column Environment[edit]

General Tips[edit]

  • By far the easiest way to learn how to do something is to go to the source editor for another wikipedia page, say Decision tree, and find the relevant section in the source code. You can paste this code into your sandbox article to see what happens. You can get a sense of what the article will look like by clicking "Show Preview" in the editor. If you publish an edit that you would like to revert, you can always go to Version history "undo."
  • Don't worry about knowing all the details and features of wikipedia editing and templates. Most users (myself included) will only need a small fraction of the editing features available. Focus mostly on writing, and look up information as needed.
  • Wikipedia has lots of material and help pages to get you started and answer syntax questions. If you want to know how to do something, or what the proper convention is, just Google, say "wikipedia help multiple columns." The help page for Columns should show up in the first result.
  • When in doubt, ping me in slack for help.

References[edit]

  1. ^ Bach, Stephen; Broecheler, Matthias; Huang, Bert; Getoor, Lise (2017). "Hinge-Loss Markov Random Fields and Probabilistic Soft Logic". Journal of Machine Learning Research. 18: 1–67.