ShortOrder

ShortOrder is an exerimental natural language conversational agent intended for domains with a fixed vocabulary of entities and a small number of intents. Uses might include ordering food from a restaurant or organizing your song collection.

The first stage of development is a set of tokenizers that detect entities, intents, and quantities. As an example, consider the following utterance, which would typically come from a speech-to-text system:

I would like a Dakota burger with no onions extra pickles fries and a coke

In this example, the utterance has no commas, since they were not provided by the speech-to-text process.

Using ShortOrder, this text might be tokenized as

[ADD_TO_ORDER] [QUANTITY(1)] [DAKOTA_BURGER(pid=4)] [QUANTITY(0)]
[SLICED_RED_ONION(pid=5201)] [QUANTITY(1)] [PICKLES(pid=5200)]
[MEDIUM_FRENCH_FRIES(pid=401)] [CONJUNCTION] [QUANTITY(1)]
[MEDIUM_COKE(1001)]

After tokenization, a parser might be able to group the tokens into a tree that reflects the speaker's intent:

[ADD_TO_ORDER]
    [QUANTITY(1)] [DAKOTA_BURGER(pid=4)]            // Burger, standalone menu item.
        [QUANTITY(0)] [SLICED_RED_ONION(pid=5201)]  //   Remove onion modification
        [QUANTITY(1)] [PICKLES(pid=5200)]           //   Add pickles modification
    [QUANTITY(1)] [MEDIUM_FRENCH_FRIES(pid=401)]    // French Fries, standalone menu item
    [QUANTITY(1)] [MEDIUM_COKE(1001)]               // Coke, standalone

Try It Out

ShortOrder is currently in the earliest stages of development, so documentation is sparse or nonexistant, and the code stability is uneven.

If you are interested in taking a look, you can clone the repo on GitHub or install ShortOrder with npm.

npm install shortorder

As of commit 85b7def2, there are two working samples, based on a ficticious restaurant. You can find the definition files for the menu, intents, attributes, and quantifiers at

• src\samples\data\menu.yaml
• src\samples\data\intents.yaml
• src\samples\data\attributes.yaml
• src\samples\data\quantifiers.yaml

Relevance Test Sample

This sample runs a suite of test utterances through the tokenization pipeline. The test utterances can be found at src\samples\data\tests.yaml.

If you've cloned the repo, you can build and run the sample as follows:

npm install
npm run compile
node build/src/samples/run_relevance_test.js

REPL Sample

This sample provides a Read-Eval-Print-Loop that runs the tokenizer on each line entered.

If you've cloned the repo, you can build and run the sample as follows:

npm run compile
node build/src/samples/repl.js

node build/src/samples/repl.js
Welcome to the ShortOrder REPL.
Type your order below.
A blank line exits.

60 items contributed 160 aliases.

% i'd like a dakota burger fries and a coke

INTENT: ADD_TO_ORDER: "i'd like"
QUANTITY: 1: "1"
ENTITY: DAKOTA_BURGER(4): "dakota burger"
ENTITY: MEDIUM_FRENCH_FRIES(401): "fries"
INTENT: CONJUNCTION: "and"
QUANTITY: 1: "1"
ENTITY: MEDIUM_COKE(1001): "coke"

% actually make that a pet chicken with extra pickles

INTENT: CANCEL_LAST_ITEM: "actually"
INTENT: RESTATE: "make that"
QUANTITY: 1: "1"
ENTITY: GRILLED_PETALUMA_CHICKEN_SANDWICH(100): "pet chicken"
QUANTITY: 1: "with"
QUANTITY: 1: "extra"
ENTITY: PICKLES(5200): "pickles"

%
bye

Tokenizer Design Notes