Merge branch 'main' of https://huggingface.co/spaces/butterswords/nlc-explorer

README.md

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 title: NLC Explorer
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+emoji: 🧭 🔍 ⁉️
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 ### A Natural Language Counterfactual Generator for Exploring Bias in Sentiment Analysis Algorithms
 
 ##### Overview
-This project is an extension of [Interactive Model Cards](https://github.com/amcrisan/interactive-model-cards). It focuses on providing a person more ways to explore the bias of a model through the generation of alternatives (technically [counterfactuals](https://plato.stanford.edu/entries/counterfactuals/#WhatCoun)). We believe the use of alternatives people can better understand the limitations of a model and develop productive skepticism around its usage and trustworthiness.
+This project is a digression from the project on [Interactive Model Cards](https://github.com/amcrisan/interactive-model-cards). It focuses on providing a person more ways to explore a model's outputs through the generation of alternatives (technically [counterfactuals](https://plato.stanford.edu/entries/counterfactuals/#WhatCoun)). We believe the use of multiple alternatives may allow people to better understand the limitations of a model and develop a sense of its trustworthiness and bias.
 
 ##### Known Limitations
 * Words not in the spaCy vocab for `en_core_web_lg` won't have vectors and so won't have the ability to create similarity scores.
 * WordNet provides many limitations due to its age and lack of funding for ongoing maintenance. It provides access to a large variety of the English language but certain words simply do not exist.
-* There are currently only 2 lists (Countries and Professions). We would like to find community curated lists for: Race, Sexual Orientation and Gender Identity (SOGI), Religion, age, and protected status.
+* There are currently only 2 lists (Countries and Professions). We would like to find community curated lists for: Race, Sexual Orientation and Gender Identity (SOGI), Religion, age, and other protected statuses.
+* We do not have a custom pipeline for Named Entity Recognition (NER), or a matcher, to identify complex terms (ex. "two spirit",  "male to female", "Asian American", etc.) and so these will not be fully available for interrogation. 
 
 
 ##### Key Dependencies and Packages