duckling
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duckling | BLINK | |
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13 | 2 | |
4,003 | 1,114 | |
0.2% | - | |
0.0 | 0.0 | |
about 1 month ago | 6 months ago | |
Haskell | Python | |
BSD 3-clause "New" or "Revised" License | MIT License |
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duckling
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Experimental library for scraping websites using OpenAI's GPT API
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 It's entity tagging but a specialised form (especially when dealing with historical documents where you may need Gregorian and Julian calendars).
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Automatisiert Kalendereinträge erstellen aus Mails mit Formatlosen Datumsangaben
Ah, sorry: https://github.com/facebook/duckling
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Transforming free-form geospatial directions into addresses - SOTA?
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.
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Programming languages endorsed for server-side use at Meta
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
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Unsplash chatbot for Discord, Pt. 2: more ways to bring pictures to Discord
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.
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Running Duckling on Windows
Try downloading the v0.2.0.0 release, extracting it somewhere, opening that location in powershell, and running these commands:
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Date extraction from text code/API's
Duckling can do your work: https://github.com/facebook/duckling
- SpaCy v3.0 Released (Python Natural Language Processing)
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New Haskell Foundation to Foster Haskell Adoption, Raises 200k USD
> It appears that the intent is to focus on pain points in the Haskell toolchain and libraries.
Good. I set myself the challenge of compiling a Haskell program [1] during the Christmas holidays. It was meant to be a "one mince pie" challenge, but after an hour I discovered the VM I used didn't have enough RAM (during compilation we were approaching 4GB), then I ran out of disk space as stack approaches 5GB & I had other stuff installed. Once a few hours had gone by (this program isn't fast to compile) I had a working program. I now have to figure out if I can distribute just the resulting binary to other servers, or if it needs other software like GHC installing. Having finished the pack of mince pies, that can wait to another day.
I know when I first started compiling C/C++ software there was a learning curve and it took hours the first time, but I found it easier to get started. With Haskell, the way one version of GHC is installed first and then Stack installs a completely isolated version is confusing; plus the inscrutable error messages (haven't got it to hand, but one means OOM but doesn't say that - it takes a Google to find the GitHub issue to work that out).
And this is before I try and experiment/decide to learn some Haskell. Apart from the error messages they're not issues with Haskell per se, but they contribute to the experience of it.
BLINK
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SpaCy v3.0 Released (Python Natural Language Processing)
there is also BLINK by Facebook
What are some alternatives?
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
ctparse - Parse natural language time expressions in python
Kornia - Geometric Computer Vision Library for Spatial AI
Giveme5W1H - Extraction of the journalistic five W and one H questions (5W1H) from news articles: who did what, when, where, why, and how?
syntaxdot - Neural syntax annotator, supporting sequence labeling, lemmatization, and dependency parsing.
semantic-source - Parsing, analyzing, and comparing source code across many languages
rules - Durable Rules Engine
laserembeddings - LASER multilingual sentence embeddings as a pip package
projects - 🪐 End-to-end NLP workflows from prototype to production
stack - The Haskell Tool Stack