Nested Propositions in Open Information Extraction

@inproceedings{Bhutani2016NestedPI,
  title={Nested Propositions in Open Information Extraction},
  author={Nikita Bhutani and H. Jagadish and Dragomir R. Radev},
  booktitle={EMNLP},
  year={2016}
}
The challenges of Machine Reading and Knowledge Extraction at a web scale require a system capable of extracting diverse information from large, heterogeneous corpora. [...] Key Method To address the lack of representation power, we propose NESTIE, which uses a nested representation to extract higher-order relations, and complex, interdependent assertions. Nesting the extracted propositions allows NESTIE to more accurately reflect the meaning of the original sentence. Our experimental study on real-world…Expand
MinIE: Minimizing Facts in Open Information Extraction
On the Limits of Aligning OpenIE Extractions with Knowledge Bases
  • 2020
Open Information Extraction from Question-Answer Pairs
Open Relation Extraction and Grounding
Constructing lexicons of relational phrases
Biomedical Information Extraction for Complex Sentences
  • 2020
Hybrid Neural Tagging Model for Open Relation Extraction.
...
1
2
3
4
...

References

SHOWING 1-10 OF 27 REFERENCES
Open Language Learning for Information Extraction
Identifying Relations for Open Information Extraction
Open Information Extraction Using Wikipedia
Open Information Extraction from the Web
Semantic Role Labeling for Open Information Extraction
Leveraging Linguistic Structure For Open Domain Information Extraction
Open Information Extraction via Contextual Sentence Decomposition
TextRunner: Open Information Extraction on the Web
...
1
2
3
...