Papers by Ozan İrsoy
Weakly Supervised Headline Dependency Parsing (2022.findings-emnlp)
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| Challenge: | English news headlines have unique syntactic properties documented in linguistics literature since the 1930s. |
| Approach: | They propose to provide the first news headline corpus of annotated syntactic dependency trees to evaluate existing NLP parsers on news headlines. |
| Outcome: | The proposed method improves performance across different news outlets, but is moderated by constructions idiosyncratic to outlet. |
Learning Syntax from Naturally-Occurring Bracketings (2021.naacl-main)
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| Challenge: | a new method for learning naturally-occurring bracketings is developed . it uses noisy and incomplete data to induce syntactic structures . |
| Approach: | They propose a partial-brackets-aware structured ramp loss in learning to address this challenge . they show that distantly-supervised models trained on naturally-occurring bracketing data are more accurate . constituency is a foundational building block for phrase-structure grammars, they argue . |
| Outcome: | The proposed model achieves an unlabeled F1 score for constituency parsing on the English WSJ corpus. |
Disentangling Online Chats with DAG-structured LSTMs (2021.starsem-1)
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| Challenge: | a number of messaging systems allow fast and synchronous textual communication but they often have a more complicated structure in which independent sub-conversations are interwoven with one another. |
| Approach: | They propose a model that can handle directed acyclic dependencies and integrates structured information into the conversation. |
| Outcome: | The proposed model achieves state-of-the-art status on the task of recovering reply-to relations and is competitive on other disentanglement metrics. |
Diversity-Aware Batch Active Learning for Dependency Parsing (2021.naacl-main)
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| Challenge: | a high annotation cost for dependency parsers is a challenge . batch active learning (AL) is based on batch mode, which is more efficient for annotators to label in bulk. |
| Approach: | They propose to reduce the number of labeled examples needed to train a strong dependency parser using batch active learning. |
| Outcome: | The proposed approach improves on an English newswire corpus by enforcing diversity in the sampled batches. |