# Hierarchy Builder: Organizing Textual Spans into a Hierarchy to Facilitate Navigation

arXiv: https://arxiv.org/abs/2309.10057 · HTML: https://mlsanity.com/paper/2309.10057/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 18 references that are in the map.
- First posted on arXiv 18 Sep 2023.

## Builds on (most cited first, 7 of 7)

- [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://mlsanity.com/paper/1606.05250/) (2016)
- [SciBERT: A Pretrained Language Model for Scientific Text](https://mlsanity.com/paper/1903.10676/) (2019)
- [Self-Alignment Pretraining for Biomedical Entity Representations](https://mlsanity.com/paper/2010.11784/) (2020)
- [Syntactic Search by Example](https://mlsanity.com/paper/2006.03010/) (2020)
- [Interactive Extractive Search over Biomedical Corpora](https://mlsanity.com/paper/2006.04148/) (2020)
- [Neural Extractive Search](https://mlsanity.com/paper/2106.04612/) (2021)
- [Lookup or Exploratory: What is Your Search Intent?](https://mlsanity.com/paper/2110.04640/) (2021)

## Abstract (arXiv)

Information extraction systems often produce hundreds to thousands of strings on a specific topic. We present a method that facilitates better consumption of these strings, in an exploratory setting in which a user wants to both get a broad overview of what's available, and a chance to dive deeper on some aspects. The system works by grouping similar items together and arranging the remaining items into a hierarchical navigable DAG structure. We apply the method to medical information extraction.