Information extraction (IE) aims to extract structural knowledge (such as entities, relations,
and events) from plain natural language texts. Recently, generative Large Language Models …

A long standing goal of the data management community is to develop general, automated
systems that ingest semi-structured documents and output queryable tables without human …

News dissemination in social media causes fluctuations in financial markets.(Scope) Recent
advanced methods in deep learning-based natural language processing have shown …

Open information extraction is an important NLP task that targets extracting structured
information from unstructured text without limitations on the relation type or the domain of the …

Regulatory documents play a significant role in securing engineering project quality,
standard process management and long-term sustainable developments. With the …

Open Information Extraction (OIE) task aims at extracting structured facts from unstructured
text, typically in the form of (subject, relation, object) triples. Despite the potential of large …

Multimodal Knowledge Graph Construction (MKGC) involves creating structured
representations of entities and relations using multiple modalities, such as text and images …

Event extraction (EE) is crucial to downstream tasks such as new aggregation and event
knowledge graph construction. Most existing EE datasets manually define fixed event types …

Building document-grounded dialogue systems have received growing interest as
documents convey a wealth of human knowledge and commonly exist in enterprises …

Abstract Information extraction (IE) encounters challenges due to the variety of schemas and
objectives that differ across tasks. Recent advancements hint at the potential for universal …