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NFDI4DS

ST KGQA

ST KGQA

2024-12-01
1 min read

NFDI4DS partners organize a challenge co-located with ACL2024 in Bangkok, Thailand, 11-16 August, 2024.

TextGraph fosters investigation of synergies between methods for text and graph processing. This edition focuses on the fusion of LLMs with KGs. In line with this goal we propose a shared task on Text-Graph Representations for Knowledge Graph Question Answering (KGQA).

The shared task is to select a KG entity (out of several candidates) which correspond to an answer given a textual question. The specificity of the task, is that for each question-answer (Q-A) pair not only a textual Q-A pair is given but also a graph of shortest paths in the KG from entities in query to the LLM-generated candidate entity (including links of the intermediate nodes). This way, participants easily may experiment with various strategies of text-graph modality fusion for the given task in a controllable manner.

So the goal is to learn how LLMs output can be enhanced with KGs. We propose a convenient testbed for it by pre-extracting the graph as there are many ways how this extraction can be done fragmenting the text-graph modality data fusion experiments.

Find detailed information on the workshop page: https://sites.google.com/view/textgraphs2024/home/shared-task

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