Heng Ji

Leveraging Entity Linking and Related Language Projection to Improve Name Transliteration

2016

Traditional name transliteration methods largely ignore source context information and inter-dependency among entities for entity disambiguation. We propose a novel approach to leverage state-of-the-art Entity Linking (EL) techniques to automatically correct name transliteration results, using …

Acquiring Background Knowledge to Improve Moral Value Prediction

2017 · arXiv (Cornell University)

In this paper, we address the problem of detecting expressions of moral values in tweets using content analysis. This is a particularly challenging problem because moral values are often only implicitly signaled in language, and …

Keep Meeting Summaries on Topic: Abstractive Multi-Modal Meeting Summarization

2019

Transcripts of natural, multi-person meetings differ significantly from documents like news articles, which can make Natural Language Generation models generate unfocused summaries. We develop an abstractive meeting summarizer from both videos and audios of meeting …

The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Prediction

2021 · arXiv (Cornell University)

Event schemas encode knowledge of stereotypical structures of events and their connections. As events unfold, schemas are crucial to act as a scaffolding. Previous work on event schema induction focuses either on atomic events or …

Word Embeddings Are Steers for Language Models

2023 · arXiv (Cornell University)

Language models (LMs) automatically learn word embeddings during pre-training on language corpora. Although word embeddings are usually interpreted as feature vectors for individual words, their roles in language model generation remain underexplored. In this work, …

Human-in-the-loop Schema Induction

2023

Tianyi Zhang, Isaac Tham, Zhaoyi Hou, Jiaxuan Ren, Leon Zhou, Hainiu Xu, Li Zhang, Lara J. Martin, Rotem Dror, Sha Li, Heng Ji, Martha Palmer, Susan Windisch Brown, Reece Suchocki, Chris Callison-Burch. Proceedings of the …

CoType

2017

Extracting entities and relations for types of interest from text is important for understanding massive text corpora. Traditionally, systems of entity relation extraction have relied on human-annotated corpora for training and adopted an incremental pipeline. …

Cross-lingual Name Tagging and Linking for 282 Languages

2017

The ambitious goal of this work is to develop a cross-lingual name tagging and linking framework for 282 languages that exist in Wikipedia. Given a document in any of these languages, our framework is able …

Visual Attention Model for Name Tagging in Multimodal Social Media

2018

Everyday billions of multimodal posts containing both images and text are shared in social media sites such as Snapchat, Twitter or Instagram. This combination of image and text in a single message allows for more …

CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases

2016 · arXiv (Cornell University)

Extracting entities and relations for types of interest from text is important for understanding massive text corpora. Traditionally, systems of entity relation extraction have relied on human-annotated corpora for training and adopted an incremental pipeline. …

A Dependency-Based Neural Network for Relation Classification

2015

Yang Liu, Furu Wei, Sujian Li, Heng Ji, Ming Zhou, Houfeng Wang. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume …

Zero-Shot Transfer Learning for Event Extraction

2018

Most previous supervised event extraction methods have relied on features derived from manual annotations, and thus cannot be applied to new event types without extra annotation effort. We take a fresh look at event extraction …

Low-Resource Name Tagging Learned with Weakly Labeled Data

2019

Yixin Cao, Zikun Hu, Tat-seng Chua, Zhiyuan Liu, Heng Ji. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

Cross-lingual Structure Transfer for Relation and Event Extraction

2019

Ananya Subburathinam, Di Lu, Heng Ji, Jonathan May, Shih-Fu Chang, Avirup Sil, Clare Voss. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language …

A Joint Neural Model for Information Extraction with Global Features

2020

Most existing joint neural models for Information Extraction (IE) use local task-specific classifiers to predict labels for individual instances (e.g., trigger, relation) regardless of their interactions. For example, a VICTIM of a DIE event is …

Neural-Answering Logical Queries on Knowledge Graphs

2021

Logical queries constitute an important subset of questions posed in knowledge graph question answering systems. Yet, effectively answering logical queries on large knowledge graphs remains a highly challenging problem. Traditional subgraph matching based methods might …

Efficient Attentions for Long Document Summarization

2021

Luyang Huang, Shuyang Cao, Nikolaus Parulian, Heng Ji, Lu Wang. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2021.

Document-Level Event Argument Extraction by Conditional Generation

2021

Event extraction has long been treated as a sentence-level task in the IE community. We argue that this setting does not match human information seeking behavior and leads to incomplete and uninformative extraction results. We …