lpaqa's Introduction

LPAQA: Language model Prompt And Query Archive

This repository contains data and code for the paper How Can We Know What Language Models Know?

Install

Our repository is based on LAMA. Please download our fork from here and follow the instructions to set up the environment and download pre-trained language models.

# clone LPAQA
git clone https://github.com/jzbjyb/LPAQA.git LPAQA
# clone LAMA
git clone https://github.com/jzbjyb/LAMA.git LAMA
pushd LAMA && git reset --hard b6b1885c64de5981f249a8b65de25cb0802b4bd5 && rm -rf .git && popd
mv LAMA/* LPAQA/ && rm -rf LAMA
# follow the instructions to install
cd LPAQA
./setup.sh

Retrieve factual knowledge from LMs

For example, to query the owner of MSN (Microsoft is the answer), you can either use manually created prompts (x is owned by y):

python lama/eval_generation.py --lm bert --t "MSN is owned by [MASK]."

or use LPAQA that ensembles a diversity of prompts:

# mined prompts
python lama/eval_ensemble.py --lm bert --subject MSN --relation P127 --prompts prompt/mine
# paraphrased prompts
python lama/eval_ensemble.py --lm bert --subject MSN --relation P127 --prompts prompt/paraphrase

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