scrapeghost
duckling
scrapeghost | duckling | |
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10 | 13 | |
1,396 | 4,019 | |
- | 0.2% | |
8.2 | 0.0 | |
5 months ago | 3 months ago | |
Python | Haskell | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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scrapeghost
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Those of you who have developed product features using GPT4 API (or failed to do so), how did it go?
Not my project but an ex-colleague has been having some success in this direction: https://jamesturk.github.io/scrapeghost/
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What are the best tools for web scraping and analysis of natural language to populate a dataset?
Yes, there is something like that available - ScrapeGhost.
- FLaNK Stack Weekly 3 April 2023
- Scraping Websites Using GPT
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@TwitterDev Announces New Twitter API Tiers
With AI scraping, tools can be far more resilient than soon enough to minor dom changes. See - https://jamesturk.github.io/scrapeghost/.
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Experimental library for scraping websites using OpenAI's GPT API
Their ToS mentions scraping but it pertains to scraping their frontend instead of using their API, which they don't want you to do.
Also - this library requests the HTML by itself [0] and ships it as a prompt but with preset system messages as the instruction [1].
[0] - https://github.com/jamesturk/scrapeghost/blob/main/src/scrap...
[1] - https://github.com/jamesturk/scrapeghost/blob/main/src/scrap...
- scrapeghost. Web scrape using gpt-4 (experimental)
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 It's entity tagging but a specialised form (especially when dealing with historical documents where you may need Gregorian and Julian calendars).
[0] https://github.com/facebook/duckling
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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
- Data Cleaning using Machine Learning?
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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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Dependencies difference between cabal and stack
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.
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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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[ANN] Duckling v0.2.0.0 released
Duckling (https://github.com/facebook/duckling) is a library for parsing text into structured data.
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Extract name:value relationships from plain text
If you really want high precision, Duckling is a good project to check out https://github.com/facebook/duckling
What are some alternatives?
autoscraper - A Smart, Automatic, Fast and Lightweight Web Scraper for Python
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
tmx-solver - ThreatMetrix (anti-bot/fraud-detection) solver, deobfuscator & data harvester
ctparse - Parse natural language time expressions in python
wikipedia_ql - Query language for efficient data extraction from Wikipedia
Giveme5W1H - Extraction of the journalistic five W and one H questions (5W1H) from news articles: who did what, when, where, why, and how?
Bandwhich - Terminal bandwidth utilization tool
syntaxdot - Neural syntax annotator, supporting sequence labeling, lemmatization, and dependency parsing.
bpytop - Linux/OSX/FreeBSD resource monitor
Kornia - Geometric Computer Vision Library for Spatial AI
exiftool - ExifTool meta information reader/writer
BLINK - Entity Linker solution