# Sangrahaka: A Tool for Annotating and Querying Knowledge Graphs

arXiv: https://arxiv.org/abs/2107.02782 · HTML: https://mlsanity.com/paper/2107.02782/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 26 references that are in the map.
- First posted on arXiv 6 Jul 2021.

## Built on by (most cited first, 4 of 4)

- [SanskritShala: A Neural Sanskrit NLP Toolkit with Web-Based Interface for Pedagogical and Annotation Purposes](https://mlsanity.com/paper/2302.09527/) (2023)
- [Semantic Annotation and Querying Framework based on Semi-structured Ayurvedic Text](https://mlsanity.com/paper/2202.00216/) (2022)
- [A Case Study of Cross-Lingual Zero-Shot Generalization for Classical Languages in LLMs](https://mlsanity.com/paper/2505.13173/) (2025)
- [Antarlekhaka: A Comprehensive Tool for Multi-task Natural Language Annotation](https://mlsanity.com/paper/2310.07826/) (2023)

## Abstract (arXiv)

In this work, we present a web-based annotation and querying tool Sangrahaka. It annotates entities and relationships from text corpora and constructs a knowledge graph (KG). The KG is queried using templatized natural language queries. The application is language and corpus agnostic, but can be tuned for special needs of a specific language or a corpus. A customized version of the framework has been used in two annotation tasks. The application is available for download and installation. Besides having a user-friendly interface, it is fast, supports customization, and is fault tolerant on both client and server side. The code is available at https://github.com/hrishikeshrt/sangrahaka and the presentation with a demo is available at https://youtu.be/nw9GFLVZMMo.