What flavor of ice cream is AI?

For Natural Language Processing and AI analysis of extracted Corpus of text from Files, metadata Description fields or similar textual bodies i started building a few Search API Solr Post Processors that can deal with this, all under the umbrella of the Strawberryfield Runners module for 1.0.0. PS: Ping me for a showcase of the proof of concept i have running in AWS

But to make this an option for people testing-using or just admiring archipelago (yeah.. not sure how many) i want to dockerize these needs through an extra additional docker-compose.yml that can be appended via the -f option when doing and docker-compose up -d

What i need?

This

Our own local dbpedia-spotlight (for Semantic annotation which include immediately links to WIKIDATA too) exposed on port 2231 internally it runs on 80. i think we should allow people a few options
- https://hub.docker.com/r/dbpedia/spotlight-multilingual-databus Which is a multi lingual version but can be quite heavy on storage, or
- https://hub.docker.com/r/dbpedia/spotlight-spanish (no fear there is also an english one..) based on your primary language
https://github.com/web64/nlpserver dockerized (have not found an image so we have to built our own based on Alpine LInux to make it small and fast) and put/tested here https://github.com/esmero/archipelago-docker-images . This runs on port 6400 so would love to have it exposed at :2331

The idea here is basically not everyone needs fancy robots and AI getting names and links from their metadata, but some could need. I'm working on formalizing (and generalizing) the life code i have. I like the fact that it integrates good into the SBF runners idea but also forced me to make some changes there, like how/when things run and i found myself quite happy seeing that actually a lot can go directly to Solr instead of being saved on metadata but other things need to go into permanent storage.

Not the place (i know) but this also open a chance of working again on my idea that AI/NPL generated data needs to be tagged/classified and exposed to the world as such. Means i'm adding provenance, how it was processed, version of the software, etc to an upper structure of the JSON. That way we know and we can keep a separation of human generated classification v/s machine one. Machines are not always quite aware of context so the level of trust we can put on this data will vary a lot, so good we can pass that back to the end user.

@alliomeria because of metadata discussion and @giancarlobi since i think you will like this. Should be able to add code to https://github.com/esmero/strawberry_runners/tree/ISSUE-4 soon with the full refactor and the new plugins.I do have high hopes here!

esmero / archipelago-deployment

Add needed infrastructure for NLP/ENTITY extraction in our docker-compose #62

What flavor of ice cream is AI?

What i need?