duckling VS semantic-source

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 It's entity tagging but a specialised form (especially when dealing with historical documents where you may need Gregorian and Julian calendars).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

One production example I know: GitHub code navigation is written in Haskell https://github.com/github/semantic

ah, easy. it's because support has not been added into https://github.com/github/semantic which is the tech that powers the GitHub UI. Adding support is pretty easy/mainly glue code [1] that imports the tree sitter API.

[1] https://github.com/github/semantic/blob/793a876ae45d38a6bd17...

GitHub used Haskell for implementing Semantic, a command-line tool for parsing, analyzing, and comparing source code.

As far as engineering effort, you can read this GitHub comment for an overview of where we’d like to take the project in the future. The tl;dr here is that the open sum type view of the world made it very concise to fold over syntax trees (since such a view of data is ultimately unityped, recursion schemes Just Work), but the tradeoff thus associated—namely, that you have to parse a concrete syntax tree into an open-sum view (a complicated and painful-to-read process), that you can never really be sure how a given syntax tree is shaped, and that the types don’t help you nearly as much as they could—proved to be too onerous to deal with. Going forward, we’re generating syntax types from the AST once per target language, and working on an abstraction (probably via this generated code; I made five separate efforts at using Generics for this, and failed every time) that recovers at least some of the convenience of recursion schemes. It turns out that recursion schemes over a mutually recursive syntax tree—as pretty much every language’s syntax trees are, in practice—are pretty much an unsolved problem, especially when extended to languages like TypeScript, which have hundreds of different syntax nodes.

Meanwhile their Tree-Sitter-based semantic parser[1] looks abandoned. There is even rotting for years pull request[2] adding support of the same stack graphs into it.

[1] https://github.com/github/semantic

[2] https://github.com/github/semantic/pull/535

The semantic team at GitHub uses it for statically analyzing the dozens of languages that end up in GitHub repositories: https://github.com/github/semantic/blob/eaf13783838861fe5eb6cd46d59354774a8eb88d/docs/why-haskell.md

Yesterday I was looking for some examples of projects using tree-sitter (which is C) when I found GitHub's semantic, used to analyze and compare source code, and written in Haskell: https://github.com/github/semantic/