Papers by Laura Ana Maria Bostan
DERE: A Task and Domain-Independent Slot Filling Framework for Declarative Relation Extraction (D18-2)
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| Challenge: | Comparability of models across tasks is lacking in most machine learning systems for natural language processing. |
| Approach: | They propose a framework for declarative specification and compilation of template-based information extraction that uses a generic specification language for the task and for data annotations in terms of spans and frames. |
| Outcome: | The proposed framework enables representation of a large variety of natural language processing tasks. |
GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception (2020.lrec-1)
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| Challenge: | Fewer studies address emotions as a phenomenon to be tackled with structured learning, which can be explained by the lack of relevant datasets. |
| Approach: | They propose to annotate 5000 English news headlines with their associated emotions, the corresponding emotion experiencers and textual cues, related emotion causes and targets, and the reader’s perception of the emotion of the headline. |
| Outcome: | The proposed method enables further research on emotion classification, emotion intensity prediction, emotion cause detection and supports qualitative studies. |
Automatic Section Recognition in Obituaries (2020.lrec-1)
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| Challenge: | Obituaries contain information about people’s values across times and cultures, which makes them useful for exploring cultural history. |
| Approach: | They propose to use a convolutional neural network to recognize these sections in obituaries to improve their annotation. |
| Outcome: | The proposed model outperforms bag-of-words and embedding-based BiLSTMs and BiLStm-CRFs with a micro F1 = 0.81. |