Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

In this work we propose a novel end-to-end multi-stage Knowledge Graph (KG) generation
system from textual inputs, separating the overall process into two stages. The graph nodes …

Task-oriented dialog (TOD) systems often require interaction with an external knowledge
base to retrieve necessary entity (eg, restaurant) information to support the response …

We propose DEER (Descriptive Knowledge Graph for Explaining Entity Relationships)-an
open and informative form of modeling entity relationships. In DEER, relationships between …

Automatic construction of relevant Knowledge Bases (KBs) from text, and generation of
semantically meaningful text from KBs are both long-standing goals in Machine Learning. In …

Relations between entities can be represented by different instances, eg, a sentence
containing both entities or a fact in a Knowledge Graph (KG). However, these instances may …

Fine-grained few-shot entity extraction in the chemical domain faces two unique challenges.
First, compared with entity extraction tasks in the general domain, sentences from chemical …

Word associations are among the most common paradigms to study the human mental
lexicon. While their structure and types of associations have been well studied, surprisingly …

In this work we address the problem of Knowledge Graph (KG) construction from text,
proposing a novel end-to-end multi-stage Grapher system, that separates the overall …

Term extraction is an information extraction task at the root of knowledge discovery
platforms. Developing term extractors that are able to generalize across very diverse and …