mirage VS duckling

Interesting, and thanks.

I didn't know about those. I kind of thought you may have used MirageOS, which I had read about earlier. It is done in OCaml.

https://mirage.io/

Unix system programming in OCaml (2014)

https://ocaml.github.io/ocamlunix/

"MirageOS is a library operating system that constructs unikernels for secure, high-performance network applications across a variety of cloud computing and mobile platforms."

https://mirage.io/

That was/is part of the promise of the whole unikernel thing, no?

https://mirage.io/ or similar could then let you boot your database. That said, it's not really taken off from what I can tell, so I'm guessing there's more to it than that.

MirageOS is not Rust, but in the ballpark!

https://mirage.io/

OCaml MirageOS? https://mirage.io/

MirageOS is a runtime for OCaml to create unikernels. They describe themselves as "library operating system". Probably not quite what you were asking for, but I think it's quite interesting for certain use cases (e.g. running services as standalone unikernels in VMs or embedded devices instead of "traditional" programs on top of a general purpose OS).

For the reasons others have said I don't see it replacing 'traditional' scraping soon. But I am looking forward to it replacing current methods of extracting data from the scraped content.

I've been using Duckling [0] for extracting fuzzy dates and times from text. It does a good job but I needed a custom build with extra rules to make that into a great job. And that's just for dates, 1 of 13 dimensions supported. Being able to use an AI that handles them with better accuracy will be fantastic.

Does a specialised model trained to extract times and dates already exist? It's entity tagging but a specialised form (especially when dealing with historical documents where you may need Gregorian and Julian calendars).

[0] https://github.com/facebook/duckling

Ah, sorry: https://github.com/facebook/duckling

To understand what relative distance and direction is indicated from the reference point, I'd look into something like Facebook & Wit.AI's Duckling, and a custom classifier to identify if it's on the reference point ("corner of"), or some distance from ("200 meters southwest"). If you can parse out a distance and direction, then it's all logic to plot the point.

It also powers the backend of Wit.ai which FB owns. Wit's open-source entity parser, duckling, is written entirely in Haskell. https://github.com/facebook/duckling

Our RandomPicForLater intent will have one slot called reminderTime and will be of type @duckling.time. Duckling is a library that extracts entities from text, and it is one of the tools used in JAICP for this purpose. Entity types in Duckling are called dimensions and there's a number of them built in, among them is Time which suits us perfectly since we need to ask users when they want us to schedule a post for and then parse a text input into a datetime object.

I'm working on a pretty interesting project right now and I'm having different results depending on the build tool used: with cabal, the test suite fails but it passes with stack.

Try downloading the v0.2.0.0 release, extracting it somewhere, opening that location in powershell, and running these commands:

Duckling (https://github.com/facebook/duckling) is a library for parsing text into structured data.

If you really want high precision, Duckling is a good project to check out https://github.com/facebook/duckling