Search Results for author:
Found 28 papers, 7 papers with code
Exploiting Image–Text Synergy for Contextual Image Captioning
Modern web content - news articles, blog posts, educational resources, marketing brochures - is predominantly multimodal.
Answering Count Queries with Explanatory Evidence
A challenging case in web search and question answering are count queries, such as \textit{"number of songs by John Lennon"}.
Materialized Knowledge Bases from Commonsense Transformers
Starting from the COMET methodology by Bosselut et al. (2019), generating commonsense knowledge directly from pre-trained language models has recently received significant attention.
Refined Commonsense Knowledge from Large-Scale Web Contents
Prior works like ConceptNet, COMET and others compiled large CSK collections, but are restricted in their expressiveness to subject-predicate-object (SPO) triples with simple concepts for S and strings for P and O.
Predicting Document Coverage for Relation Extraction
We employ methods combining features with statistical models like TF-IDF and language models like BERT.
Language Models As or For Knowledge Bases
Pre-trained language models (LMs) have recently gained attention for their potential as an alternative to (or proxy for) explicit knowledge bases (KBs).
KnowFi: Knowledge Extraction from Long Fictional Texts
Knowledge base construction has recently been extended to fictional domains like multi-volume novels and TV/movie series, aiming to support explorative queries for fans and sub-culture studies by humanities researchers.
Inside ASCENT: Exploring a Deep Commonsense Knowledge Base and its Usage in Question Answering
ASCENT is a fully automated methodology for extracting and consolidating commonsense assertions from web contents (Nguyen et al., WWW 2021).
Commonsense Knowledge Base Construction in the Age of Big Data
Compiling commonsense knowledge is traditionally an AI topic approached by manual labor.
SANDI: Story-and-Images Alignment
The Internet contains a multitude of social media posts and other of stories where text is interspersed with images.
Information to Wisdom: Commonsense Knowledge Extraction and Compilation
Commonsense knowledge is a foundational cornerstone of artificial intelligence applications.
Advanced Semantics for Commonsense Knowledge Extraction
Commonsense knowledge (CSK) about concepts and their properties is useful for AI applications such as robust chatbots.
ENTYFI: A System for Fine-grained Entity Typing in Fictional Texts
Fiction and fantasy are archetypes of long-tail domains that lack suitable NLP methodologies and tools.
Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases
Equipping machines with comprehensive knowledge of the world's entities and their relationships has been a long-standing goal of AI.
Counting Query Answers over a DL-Lite Knowledge Base (extended version)
Counting answers to a query is an operation supported by virtually all database management systems.
CounQER: A System for Discovering and Linking Count Information in Knowledge Bases
Predicate constraints of general-purpose knowledge bases (KBs) like Wikidata, DBpedia and Freebase are often limited to subproperty, domain and range constraints.
Uncovering Hidden Semantics of Set Information in Knowledge Bases
This paper focuses on set-valued predicates, i. e., the relationship between an entity and a set of entities.
Enriching Knowledge Bases with Interesting Negative Statements
Negative statements would be important to overcome current limitations of question answering, yet due to their potential abundance, any effort towards compiling them needs a tight coupling with ranking.
Joint Reasoning for Multi-Faceted Commonsense Knowledge
Each concept is treated in isolation from other concepts, and the only quantitative measure (or ranking) of properties is a confidence score that the statement is valid.
Negative Statements Considered Useful
Negative statements are useful to overcome limitations of question answering systems that are mainly geared for positive questions; they can also contribute to informative summaries of entities.
Coverage of Information Extraction from Sentences and Paragraphs
Scalar implicatures are language features that imply the negation of stronger statements, e. g., {``}She was married twice{''} typically implicates that she was not married thrice.
Story-oriented Image Selection and Placement
Multimodal contents have become commonplace on the Internet today, manifested as news articles, social media posts, and personal or business blog posts.
Commonsense Properties from Query Logs and Question Answering Forums
Commonsense knowledge about object properties, human behavior and general concepts is crucial for robust AI applications.
TiFi: Taxonomy Induction for Fictional Domains [Extended version]
Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention.
Enriching Knowledge Bases with Counting Quantifiers
In a large-scale experiment, we demonstrate the potential for knowledge base enrichment by applying CINEX to 2, 474 frequent relations in Wikidata.
Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties [Extended Version]
In this work, we have developed a human-annotated dataset of 350 preference judgments among pairs of knowledge base properties for fixed entities.
Cardinal Virtues: Extracting Relation Cardinalities from Text
Information extraction (IE) from text has largely focused on relations between individual entities, such as who has won which award.
