# Assisted Knowledge Graph Authoring: Human-Supervised Knowledge Graph Construction from Natural Language

arXiv: https://arxiv.org/abs/2401.07683 · HTML: https://mlsanity.com/paper/2401.07683/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 20 references that are in the map.
- First posted on arXiv 15 Jan 2024.

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

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference](https://mlsanity.com/paper/1704.05426/) (2017)
- [KGAT: Knowledge Graph Attention Network for Recommendation](https://mlsanity.com/paper/1905.07854/) (2019)
- [FLERT: Document-Level Features for Named Entity Recognition](https://mlsanity.com/paper/2011.06993/) (2020)
- [Web of Scholars: A Scholar Knowledge Graph](https://mlsanity.com/paper/2202.11311/) (2022)
- [REDrm FM: a Filtered and Multilingual Relation Extraction Dataset](https://mlsanity.com/paper/2306.09802/) (2023)

## Built on by (most cited first, 1 of 1)

- [MUSEKG: A Knowledge Graph Over Museum Collections](https://mlsanity.com/paper/2511.16014/) (2025)

## Abstract (arXiv)

Encyclopedic knowledge graphs, such as Wikidata, host an extensive repository of millions of knowledge statements. However, domain-specific knowledge from fields such as history, physics, or medicine is significantly underrepresented in those graphs. Although few domain-specific knowledge graphs exist (e.g., Pubmed for medicine), developing specialized retrieval applications for many domains still requires constructing knowledge graphs from scratch. To facilitate knowledge graph construction, we introduce WAKA: a Web application that allows domain experts to create knowledge graphs through the medium with which they are most familiar: natural language.