# Term Set Expansion based NLP Architect by Intel AI Lab

arXiv: https://arxiv.org/abs/1808.08953 · HTML: https://mlsanity.com/paper/1808.08953/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Aug 2018.

## Built on by (most cited first, 11 of 11)

- [Contrastive Learning with Hard Negative Entities for Entity Set Expansion](https://mlsanity.com/paper/2204.07789/) (2022)
- [Automatic Context Pattern Generation for Entity Set Expansion](https://mlsanity.com/paper/2207.08087/) (2022)
- [MESED: A Multi-modal Entity Set Expansion Dataset with Fine-grained Semantic Classes and Hard Negative Entities](https://mlsanity.com/paper/2307.14878/) (2023)
- [A Unified Taxonomy-Guided Instruction Tuning Framework for Entity Set Expansion and Taxonomy Expansion](https://mlsanity.com/paper/2402.13405/) (2024)
- [From Retrieval to Generation: Efficient and Effective Entity Set Expansion](https://mlsanity.com/paper/2304.03531/) (2023)
- [Entity Set Co-Expansion in StackOverflow](https://mlsanity.com/paper/2212.02271/) (2022)
- [UltraWiki: Ultra-fine-grained Entity Set Expansion with Negative Seed Entities](https://mlsanity.com/paper/2403.04247/) (2024)
- [Characterizing Nexus of Similarity within Knowledge Bases: A Logic-based Framework and its Computational Complexity Aspects](https://mlsanity.com/paper/2303.10714/) (2023)
- [APack: Off-Chip, Lossless Data Compression for Efficient Deep Learning Inference](https://mlsanity.com/paper/2201.08830/) (2022)
- [GausSetExpander: A Simple Approach for Entity Set Expansion](https://mlsanity.com/paper/2202.13649/) (2022)
- [Advancing Relation Extraction through Language Probing with Exemplars from Set Co-Expansion](https://mlsanity.com/paper/2308.11720/) (2023)

## Abstract (arXiv)

We present SetExpander, a corpus-based system for expanding a seed set of terms into amore complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to-end workflow. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes.SetExpander has been used successfully in real-life use cases including integration into an automated recruitment system and an issues and defects resolution system. A video demo of SetExpander is available at https://drive.google.com/open?id=1e545bB87Autsch36DjnJHmq3HWfSd1Rv (some images were blurred for privacy reasons)