Papers with demonstration system
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. |
SARAL: A Low-Resource Cross-Lingual Domain-Focused Information Retrieval System for Effective Rapid Document Triage (P19-3)
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Elizabeth Boschee, Joel Barry, Jayadev Billa, Marjorie Freedman, Thamme Gowda, Constantine Lignos, Chester Palen-Michel, Michael Pust, Banriskhem Kayang Khonglah, Srikanth Madikeri, Jonathan May, Scott Miller
| Challenge: | a new cross-lingual information retrieval system for low-resource languages is available in less-frequently-taught languages . a multilingual system can search for relevant information in a haystack of documents in swahili or Somali . human-driven approaches to this problem are complicated in 'low-resourced' languages aaron sagar: "the key role played by humans in triaging results is complicated" |
| Approach: | They propose an end-to-end cross-lingual information retrieval system for low-resource languages . the system enables English speakers to search foreign language repositories using English queries . it summarizes the retrieved documents in English with respect to a particular information need . |
| Outcome: | The proposed system achieves top performance in the most recent IARPA MATERIAL CLIR+summarization evaluations. |
Visualizing Trends of Key Roles in News Articles (D19-3)
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| Challenge: | a demonstration system visualizes news trend of key roles based on natural language processing techniques . semantic role labelling and word embeddings can help users understand news topics . |
| Approach: | They propose a system that visualizes the news trend of key roles based on natural language processing techniques. |
| Outcome: | The proposed system analyzes the news trend of key roles using semantic role labelling . it also analyzes how similarities between key roles and news topics change over time . |