Papers by Haoling Qiu
ZS4IE: A toolkit for Zero-Shot Information Extraction with simple Verbalizations (2022.naacl-demo)
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| Challenge: | Information Extraction (IE) analysts use supervised machine learning to define the schema and build a training corpus with annotated examples. |
| Approach: | They propose a workflow where the analyst verbalizes the entities/relations, which are then used by a Textual Entailment model to perform zero-shot IE. |
| Outcome: | The proposed workflow performs very well on four IE tasks with a single user interface and a video demonstration is available on vimeo. |
Factuality Assessment as Modal Dependency Parsing (2021.acl-long)
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| Challenge: | a critical step towards factuality assessment is to determine the factuality of events in text. |
| Approach: | They propose a modal dependency parsing task that assesses the factuality of events in text . they crowdsource a large-scale data set annotated with modal dependence structures . |
| Outcome: | The proposed model outperforms the pipeline model in factuality assessment . the proposed model is based on a crowdsourced dataset . |
Annotating Temporal Dependency Graphs via Crowdsourcing (2020.emnlp-main)
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| Challenge: | Existing temporal annotation schemes have been limited due to the complexity of temporal relations between events. |
| Approach: | They propose to build a corpus of Wikinews articles annotated with temporal dependency graphs . they also propose a crowdsourcing strategy to annotate TDGs based on the corpus . |
| Outcome: | The proposed method achieves a good trade-off between completeness and practicality in temporal annotation. |
ExcavatorCovid: Extracting Events and Relations from Text Corpora for Temporal and Causal Analysis for COVID-19 (2021.emnlp-demo)
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| Challenge: | a new machine reading system ingests open-source text documents to analyze COVID-19 events . the system extracts COVId-19 related events and relations between them . |
| Approach: | They propose a machine reading system that ingests open-source text documents and extracts COVID-19 related events and relations between them. |
| Outcome: | The proposed system extracts COVID-19 related events and relations from open-source text . it will help government agencies alleviate the information overload and respond to COVId-19 . |
Towards Machine Reading for Interventions from Humanitarian-Assistance Program Literature (D19-1)
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| Challenge: | a complex socio-political system is causing problems such as food insecurity . a first step is to extract past interventions and when and where they have been applied . |
| Approach: | They develop an automatic extraction system to extract past interventions from texts . they analyze a corpus annotated with interventions to foster research . |
| Outcome: | The proposed system extracts past interventions and when and where they have been applied from text . it shows early, encouraging results on extracting interventions . |
Rapid Customization for Event Extraction (P19-3)
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| Challenge: | a novel system allows users to customize event extraction to find new event types and their arguments. |
| Approach: | They propose a system that allows a user to find, expand and filter event triggers by exploring an unannotated development corpus. |
| Outcome: | The proposed system can find, expand and filter event triggers from an unannotated development corpus . it trains a generic argument attachment model for extracting Actor, Place, and Time . |