User:Navibot

This user account is a bot operated by johndburger (talk). It is used to make repetitive automated or semi-automated edits that would be extremely tedious to do manually, in accordance with the bot policy. This bot does not yet have the approval of the community, or approval has been withdrawn or expired, and therefore shouldn't be making edits that appear to be unassisted except in the operator's or its own user and user talk space.
Administrators: if this bot is making edits that appear to be unassisted to pages not in the operator's or its own userspace, please block it.

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<sum>:1

This user believes that every edit should have a summary.

Navibot is still under development. It is not running unsupervised—all of its edits are being approved by its human developer, johndburger.

The intent is that the bot find missing disambiguation entries and add them to the appropriate DAB page.

Here's an example of the kind of edit the bot is able to make. It discovered that the disambiguation page 100% did not yet point to the articles 100% (Negazione album) and 100% (compilation series), and, with human approval, it added new entries to the DAB page. The bot is currently able to determine:

Which entries are missing from which DABs (offline, by examining database dumps)
How to style the entry—in the first case, using italics, just as in the target article.
A short descriptor to attach to the entry—in this case extracted from each target's lead sentence
Where in the disambiguation page to place the new entries

All of these are currently implemented, using Postgres and the pywikipedia framework. 1 and 2 are fairly straightforward. 4 might be a little tougher for DAB pages with sections, but the bot currently punts on such pages—it will only edit DABs with a recognizably simple structure. 3 is currently working, but the descriptors are often too long, as in the example edit.

Currently all of these subtasks are accomplished with fairly simple-minded and conservative heuristics, but eventually Navibot will use machine learning to figure out how to do all of this, generalizing from the millions of existing DAB entries.

Comments are welcome on the bot's talk page.