Below is an abstract from a computer science research paper. Given this abstract, your task is to extract all unique relationships between entities of the following types:

- "USED-FOR": For instance, "Our method models user proficiency" -> ["method", "user proficiency", "USED-FOR"].
- "EVALUATE-FOR": For instance, "We evaluate our method using F1-measure" -> ["F1-measure", "method", "EVALUATE-FOR"].
- "FEATURE-OF": For instance, "prior knowledge of the model" -> ["prior knowledge", "model", "FEATURE-OF"].
- "HYPONYM-OF": For instance, "TUIT is a software library" -> ["TUIT", "software library", "HYPONYM-OF"].
- "PART-OF": For instance, "We incorporate NLU module into the system." -> ["NLU module", "system", "PART-OF"].
- "COMPARE": For instance, "Unlike the quantitative prior, the qualitative prior is often ignored" -> ["quantitative prior", "qualitative prior", "COMPARE"].
- "CONJUNCTION": For instance: "obtained from human expert or knowledge base" -> ["human expert", "knowledge base", "CONJUNCTION"].

Format your output as a json array. Each entry in the array should express a single relation, formatted as ["<Entity_A>", "<Entity_B>", "<RELATION_A_B>"]. An example output might look like:

[["neural networks", "classification", "USED-FOR"], ["neuron", "neural network", "PART-OF"]].

If no relations are found, please return an empty array [].

Abstract:

This paper introduces a system for categorizing unknown words. The system is based on a multi-component architecture where each component is responsible for identifying one class of unknown words. The focus of this paper is the components that identify names and spelling errors. Each component uses a decision tree architecture to combine multiple types of evidence about the unknown word. The system is evaluated using data from live closed captions-a genre replete with a wide variety of unknown words.
[["components", "names", "USED-FOR"], ["components", "unknown words", "USED-FOR"], ["multi-component architecture", "system", "USED-FOR"], ["components", "spelling errors", "USED-FOR"], ["decision tree architecture", "components", "USED-FOR"], ["names", "spelling errors", "CONJUNCTION"], ["components", "multi-component architecture", "PART-OF"], ["system", "categorizing unknown words", "USED-FOR"], ["live closed captions", "system", "EVALUATE-FOR"]]