Corpus ID: 13856836

Learning Biological Processes with Global Constraints

@inproceedings{Scaria2013LearningBP,
  title={Learning Biological Processes with Global Constraints},
  author={A. T. Scaria and Jonathan Berant and M. Wang and P. Clark and J. Lewis and Brittany Harding and Christopher D. Manning},
  booktitle={EMNLP},
  year={2013}
}
  • A. T. Scaria, Jonathan Berant, +4 authors Christopher D. Manning
  • Published in EMNLP 2013
  • Computer Science
  • Biological processes are complex phenomena involving a series of events that are related to one another through various relationships. [...] Key Method We represent processes by graphs whose edges describe a set of temporal, causal and co-reference event-event relations, and characterize the structural properties of these graphs (e.g., the graphs are connected).Expand Abstract
    17 Citations

    Figures, Tables, and Topics from this paper

    Modeling Biological Processes for Reading Comprehension
    • 136
    • PDF
    Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text
    • 5
    • PDF
    Lexical Event Ordering with an Edge-Factored Model
    • 11
    • Highly Influenced
    • PDF
    Annotating and Extracting Synthesis Process of All-Solid-State Batteries from Scientific Literature
    • 8
    • PDF

    References

    SHOWING 1-10 OF 41 REFERENCES
    EXTRACTING CONTEXTUALIZED COMPLEX BIOLOGICAL EVENTS WITH RICH GRAPH‐BASED FEATURE SETS
    • 48
    Event Extraction with Complex Event Classification Using Rich Features
    • 197
    • PDF
    Joint Inference for Knowledge Extraction from Biomedical Literature
    • 121
    • PDF
    Event Extraction as Dependency Parsing
    • 147
    • PDF
    Predicting Globally-Coherent Temporal Structures from Texts via Endpoint Inference and Graph Decomposition
    • 45
    • PDF
    Jointly Identifying Temporal Relations with Markov Logic
    • 130
    • Highly Influential
    • PDF
    Probabilistic Frame Induction
    • 88
    • PDF
    Classifying Temporal Relations with Rich Linguistic Knowledge
    • 37
    • Highly Influential
    • PDF
    Joint Inference for Event Timeline Construction
    • 105
    • Highly Influential
    • PDF
    Fast and Robust Joint Models for Biomedical Event Extraction
    • 103
    • PDF