DELFT: Complex Factoid QA with a Free-Text Knowledge Graph
DELFT is a factoid question answering system that combines the nuance and depth of knowledge graph QA with the broader coverage of free text. It builds a free-text knowledge graph from Wikipedia — entities as nodes, co-occurrence sentences as edges — and uses a graph neural network to reason over it.
Approach
DELFT constructs dense semantic graphs and employs graph neural networks to combine node evidence through edge sentences to determine answers. This hybrid approach outperforms pure machine reading and BERT-based baselines on entity-rich questions.
Wikipedia Graph Data
Two versions are provided:
| Version | Description | Download |
|---|---|---|
| Original links | Wikipedia article hyperlinks as edges | enwiki_links_anchor_1101.zip |
| TagMe entities | Entity annotations via TagME as edges | wiki_anchor_1101.zip |
Each entry contains: page id, title, text, anchored entities (from TagMe or article links).
Resources
- Paper: Complex Factoid Question Answering with a Free-Text Knowledge Graph — WWW 2020
- Code: github.com/henryzhao5852/DELFT
- Graph info: github.com/henryzhao5852/DELFT/tree/master/wiki_graph
Citation
@inproceedings{Zhao:Xiong:Qian:Boyd-Graber-2020,
Title = {Complex Factoid Question Answering with a Free-Text Knowledge Graph},
Author = {Chen Zhao and Chenyan Xiong and Xin Qian and Jordan Boyd-Graber},
Booktitle = {The Web Conference},
Year = {2020}
}
Contact
Chen Zhao — chenz@cs.umd.edu