# LINSPECTOR WEB: A Multilingual Probing Suite for Word Representations

arXiv: https://arxiv.org/abs/1907.11438 · HTML: https://mlsanity.com/paper/1907.11438/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jul 2019.

## Built on by (most cited first, 5 of 5)

- [Learning How to Ask: Querying LMs with Mixtures of Soft Prompts](https://mlsanity.com/paper/2104.06599/) (2021)
- [Assessing the State of Self-Supervised Human Activity Recognition using Wearables](https://mlsanity.com/paper/2202.12938/) (2022)
- [Metaphors in Pre-Trained Language Models: Probing and Generalization Across Datasets and Languages](https://mlsanity.com/paper/2203.14139/) (2022)
- [Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations](https://mlsanity.com/paper/2106.11054/) (2021)
- [Russian SuperGLUE 1.1: Revising the Lessons not Learned by Russian NLP models](https://mlsanity.com/paper/2202.07791/) (2022)

## Abstract (arXiv)

We present LINSPECTOR WEB, an open source multilingual inspector to analyze word representations. Our system provides researchers working in low-resource settings with an easily accessible web based probing tool to gain quick insights into their word embeddings especially outside of the English language. To do this we employ 16 simple linguistic probing tasks such as gender, case marking, and tense for a diverse set of 28 languages. We support probing of static word embeddings along with pretrained AllenNLP models that are commonly used for NLP downstream tasks such as named entity recognition, natural language inference and dependency parsing. The results are visualized in a polar chart and also provided as a table. LINSPECTOR WEB is available as an offline tool or at https://linspector.ukp.informatik.tu-darmstadt.de.