[willlma]

I'd love to give this a try next time I'm working on a Ruby codebase. In the meantime, I'm curious to learn more about programming by example. I found [this Microsoft paper on the subject](https://www.microsoft.com/en-us/research/wp-content/uploads/...) and have started reading it, but I'm curious if there are any reading materials you would recommend.

Specifically, I've been working on a activity tracking app that can take plain text and create structured data from it. For example

> I played tennis with Kevin and won 6-2

would turn into

```

type: tennis

opponent: Kevin

my_score: 6

their_score: 2

outcome: win

```

As you can imagine, when it comes to natural language there are many variations of I won (outcome: win), he/she/they won (outcome: loss), I was beat, etc which means that my inputs are not nearly as structured as the examples used in the paper I'm reading. Given that I'm not trying to cover every use case in the English language, which I assume would require some form of NLP, but rather just a subset that a single user would input, do you think think it would be possible to solve this with PBE techniques?

[sankha93]

Natural language is ambiguous, so I do not think any programming by example methods will work well here. I think if you are working with a limited vocabulary in the set of sentences you want to parse, it may be fine to roll out a handmade solution. For general english, there is work in intent identification in NLP that can give you structured intents from raw english text, which can then be lifted to make programs as a secondary step.

[jasfi]

You might be interested in LxAGI (https://lxagi.com) as it aims to solve this problem.