Probabilistic parser for entity detection based on Rustling (https://github.com/snipsco/rustling)
Rustling is a rust port of https://github.com/facebookincubator/duckling
| Output | OutputKind |
|---|---|
| Integer | Number |
| Float | Number |
| Ordinal | Ordinal |
| Temperature | Temperature |
| Time | Time |
| TimeInterval | Time |
| AmountOfMoney | AmountOfMoney |
| Duration | Duration |
If you want to bench the project you will need to an environment variable named SNIPS_RUSTLING_BENCH_INPUT with one of these values:
| Language | File |
|---|---|
| English | en.json |
| French | fr.json |
| Korean | ko.json |
| German | de.json |
-
Open a terminal
-
Install rust
curl https://sh.rustup.rs -sSf | sh
Select the default installation and add cargo to your source path with source $HOME/.cargo/env. You can also add this line
export PATH=$PATH:$HOME/.cargo/bin to your shell configuration .bashrc or zshrc (depending on your terminal)
- Clone this repository:
git clone git@github.com:snipsco/rustling-ontology.git
cd rustling-ontology
cargo build
It can take a while because the training for all languages takes time.
First, go to the cli folder
cd cli
Second, run this command
cargo run -- --lang en parse "tomorrow morning"
If you want to reduce the scope of rustling, you can run:
cargo run -- --lang fr parse "reserve un restaurant demain matin pour cinq personnes" -k Time,Number
If you want to see how the sentence has been parsed by rustling, you can run:
cargo run -- --lang en play "monday september the twenty sixth"
In this mode, the reference date used is the current date
go to the cli-debug folder
cd cli-debug
run this command
cargo run -- --lang en parse "tomorrow morning"
It will display how the sentence has been parsed by rustling without any ML model. (Faster to compile because the training is not done)
In debug mode, the reference date used is 2013/02/12
All original work licensed under either of
- Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT) at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.