# Intent Generation for Goal-Oriented Dialogue Systems based on Schema.org Annotations

arXiv: https://arxiv.org/abs/1807.01292 · HTML: https://mlsanity.com/paper/1807.01292/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jul 2018.

## Built on by (most cited first, 2 of 2)

- [Natural Language Sentence Generation from API Specifications](https://mlsanity.com/paper/2206.06868/) (2022)
- [Building Korean linguistic resource for NLU data generation of banking app CS dialog system](https://mlsanity.com/paper/2605.10241/) (2026)

## Abstract (arXiv)

Goal-oriented dialogue systems typically communicate with a backend (e.g. database, Web API) to complete certain tasks to reach a goal. The intents that a dialogue system can recognize are mostly included to the system by the developer statically. For an open dialogue system that can work on more than a small set of well curated data and APIs, this manual intent creation will not scalable. In this paper, we introduce a straightforward methodology for intent creation based on semantic annotation of data and services on the web. With this method, the Natural Language Understanding (NLU) module of a goal-oriented dialogue system can adapt to newly introduced APIs without requiring heavy developer involvement. We were able to extract intents and necessary slots to be filled from schema.org annotations. We were also able to create a set of initial training sentences for classifying user utterances into the generated intents. We demonstrate our approach on the NLU module of a state-of-the art dialogue system development framework.