activity
20192022
most citedTowards Lingua Franca Named Entity Recognition with BERT

27 citations · 41 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL20222 cited

A Generative Model for Relation Extraction and Classification

Jian Ni, Gaetano Rossiello, Alfio Gliozzo +1

Relation extraction (RE) is an important information extraction task which provides essential information to many NLP applications such as knowledge base population and question an…

cs.CL2020

Cross-Lingual Relation Extraction with Transformers

Jian Ni, Taesun Moon, Parul Awasthy +1

Relation extraction (RE) is one of the most important tasks in information extraction, as it provides essential information for many NLP applications. In this paper, we propose a c…

cs.CL2020

Cascaded Models for Better Fine-Grained Named Entity Recognition

Parul Awasthy, Taesun Moon, Jian Ni +1

Named Entity Recognition (NER) is an essential precursor task for many natural language applications, such as relation extraction or event extraction. Much of the NER research has…

cs.CL20202 cited

Event Presence Prediction Helps Trigger Detection Across Languages

Parul Awasthy, Tahira Naseem, Jian Ni +2

The task of event detection and classification is central to most information retrieval applications. We show that a Transformer based architecture can effectively model event extr…

cs.CL201927 cited

Towards Lingua Franca Named Entity Recognition with BERT

Taesun Moon, Parul Awasthy, Jian Ni +1

Information extraction is an important task in NLP, enabling the automatic extraction of data for relational database filling. Historically, research and data was produced for Engl…

cs.CL201910 cited

Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping

Jian Ni, Radu Florian

Relation extraction (RE) seeks to detect and classify semantic relationships between entities, which provides useful information for many NLP applications. Since the state-of-the-a…