Timeline & beta testing

[piskvorky]

Hello gentlemen,

what is the expected timeline for releasing semanticizest?

I have a client eager to try it out (because semanticizer is so slow, it's a bottleneck for them).

So I'm thinking if there's a way to share (human) resources -- maybe they could do some beta testing and benchmarking on live data, as soon as you proclaim the new semanticizest production-ready?

[larsmans]

This was planned for last month, but the deadline slipped because of other projects that had priority. My own plan is to release a bare-bones version in the second week of January.

[piskvorky]

Great, thanks Lars. Please ping me when you think it's ready (not sure what bare-bones means, perhaps that's enough).

[larsmans]

Bare-bones means we can semanticize with baseline metrics. No count-min sketch needed (you only need that for fitting more complicated models on the output of semanticizest).

[larsmans]

Hi @piskvorky, I think what we have now is ready for beta-testing. Would you like to have a try?

I was wanting to merge #22 before releasing as beta, but it needs tests and I'm not going to postpone further. The current functionality should be close to what the old semanticizer could do.

[piskvorky]

Excellent, thanks! Will check the situation with client and report back.

By the way, I remember we trained an extra model with David Graus, on Yahoo! queries. Is a similar thing possible here? Or does it not make sense? CC @graus .

[larsmans]

There's no re-ranking model in here. If you want that, you'd need to stack a model on top.

[graus]

(Which I will definitely work on if it does not magically appear -- I don't recall [if/where] this item ended up in terms of roadmap. Nor if there's a roadmap.)

[larsmans]

The idea was to provide all the information necessary for feature extraction in such a model. The thing is that we can't ship models, training data or anything, so we can't test this stuff and it will go stale.

[piskvorky]

Thanks guys.

One question: skimming the docs I can't see an obvious answer (will have to check the API in more detail later), but: I remember we had some disambiguation issues and needed semanticizer to return "unnormalized" statistics too, for some local result post-filtering.

We ended up adding something like link['unnormed'] = self.wpm.get_sense_data(ngram, sense_str) to our fork of semanticizer.

Is this already included in semanticizest, or will we have to add it again ourselves (+ pull request)? Or does this question not even make sense for the new code/approach?

[larsmans]

We're not returning that, but we should. There's an XXX in semanticizest/_semanticizer.py where it needs to be added...

[c-martinez]

Speaking of shipping models -- does anyone have an English model and wouldn't mind sharing it with me? I've tried building it myself, but my laptop crashes after processing 3920000 articles. ;-(

[larsmans]

I'm building one right now, ready in three hours. Ping me by email tomorrow morning.

[c-martinez]

Cool thanks :-)

[piskvorky]

We ran some initial checks, created the EN model, and I want to make sure I understand correctly:

semanticizEST only has a single API method, all_candidates(tokens). This returns all candidates for given tokens, no context, no disambiguation.

There's no API like in semanticizER where we send in a text (string) and it gives us back detected entities.

Is that correct?

Are you planning on extending the pipeline? What is the timeline before reaching ± semanticizER functionality? The README says that is the goal.

Thanks! CC @tgalery @graus @larsmans