duckling/README.md

Duckling

Duckling is a Haskell library that parses text into structured data.

"the first Tuesday of October"
=> {"value":"2017-10-03T00:00:00.000-07:00","grain":"day"}

Requirements

A Haskell environment is required. We recommend using stack.

Quickstart

To compile and run the binary:

$ stack build
$ stack exec duckling-example-exe

The first time you run it, it will download all required packages.

See exe/ExampleMain.hs for an example on how to integrate Duckling in your project.

Supported dimensions

Duckling supports many languages, but most don't support all dimensions yet (we need your help!).

Dimension	Example input	Example value output
Distance	"6 miles"	{"value":6,"type":"value","unit":"mile"}
Duration	"3 mins"	{"value":3,"minute":3,"unit":"minute","normalized":{"value":180,"unit":"second"}}
Email	"duckling@wit.ai"	{"value":"duckling@wit.ai"}
AmountOfMoney	"42€"	{"value":42,"type":"value","unit":"EUR"}
Numeral	"eighty eight"	{"value":88,"type":"value"}
Ordinal	"33rd"	{"value":33,"type":"value"}
PhoneNumber	"+1 (650) 123-4567"	{"value":"(+1) 6501234567"}
Quantity	"3 cups of sugar"	{"value":3,"type":"value","product":"sugar","unit":"cup"}
Temperature	"80F"	{"value":80,"type":"value","unit":"fahrenheit"}
Time	"today at 9am"	{"values":[{"value":"2016-12-14T09:00:00.000-08:00","grain":"hour","type":"value"}],"value":"2016-12-14T09:00:00.000-08:00","grain":"hour","type":"value"}
Url	"https://api.wit.ai/message?q=hi"	{"value":"https://api.wit.ai/message?q=hi","domain":"api.wit.ai"}
Volume	"4 gallons"	{"value":4,"type":"value","unit":"gallon"}

Extending Duckling

To regenerate the classifiers and run the test suite:

$ stack exec duckling-regen-exe && stack test

It's important to regenerate the classifiers after updating the code and before running the test suite.

To extend Duckling's support for a dimension in a given language, typically 2 files need to be updated:

• Duckling/<dimension>/<language>/Rules.hs
• Duckling/<dimension>/<language>/Corpus.hs

Rules have a name, a pattern and a production. Patterns are used to perform character-level matching (regexes on input) and concept-level matching (predicates on tokens). Productions are arbitrary functions that take a list of tokens and return a new token.

The corpus (resp. negative corpus) is a list of examples that should (resp. shouldn't) parse. The reference time for the corpus is Tuesday Feb 12, 2013 at 4:30am.

Duckling.Debug provides a few debugging tools:

> :l Duckling.Debug
> debug EN "in two minutes" [This Time]
in|within|after <duration> (in two minutes)
-- regex (in)
-- <integer> <unit-of-duration> (two minutes)
-- -- integer (0..19) (two)
-- -- -- regex (two)
-- -- minute (grain) (minutes)
-- -- -- regex (minutes)
[Entity {dim = "time", body = "in two minutes", value = "{\"values\":[{\"value\":\"2013-02-12T04:32:00.000-02:00\",\"grain\":\"second\",\"type\":\"value\"}],\"value\":\"2013-02-12T04:32:00.000-02:00\",\"grain\":\"second\",\"type\":\"value\"}", start = 0, end = 14}]

License

Duckling is BSD-licensed. We also provide an additional patent grant.