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Philipp Christmann's Projects

clocq icon clocq

Code for our WSDM 2022 paper. CLOCQ is a framework which allows efficient access to knowledge bases (KB) for functionalities related to question answering (QA). CLOCQ can retrieve a set of relevant facts from the KB for a given user question. Further, it provides efficient retrieval of KB-neighborhoods, KB-connectivities and labels, aliases etc.

clocq-pruning-module icon clocq-pruning-module

Implementation of a post-hoc cleaning module for CLOCQ, that can help to apply CLOCQ on entity or relation linking tasks.

convex icon convex

Code for our CIKM 2019 paper. As far as we know, CONVEX is the first unsupervised method for conversational question answering over knowledge graphs. A demo and our benchmark (and more) can be found at

convinse icon convinse

Code for our SIGIR 2022 paper. CONVINSE is a framework for conversational question answering (ConvQA) over heterogeneous information sources.

datasets icon datasets

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

explaignn icon explaignn

Code for our SIGIR 2023 paper. EXPLAIGNN provides a pipeline for conversational question answering (ConvQA) over heterogeneous sources, and code for iterative graph neural networks (GNNs). Such iterative GNNs can help to causally explaignn GNN outputs.

faith icon faith

FAITH code and data for our WWW'24 paper "Faithful Temporal Qestion Answering over Heterogeneous Sources"

fid icon fid

Fusion-in-Decoder -> To run on standard CPU/GPU

tiq icon tiq

TIQ code and data for our WWW'24 paper "Faithful Temporal Qestion Answering over Heterogeneous Sources"

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