Search Results for author:
Found 22 papers, 10 papers with code
Enriching Wikidata with Linked Open Data
We present a novel workflow that includes gap detection, source selection, schema alignment, and semantic validation.
Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning
This prunes the full self-attention structure into an order-invariant graph attention that captures the connected graph structure of cells belonging to the same row or column, and it differentiates between relevant cells and irrelevant cells from the structural perspective.
Ranked #2 on
Data-to-Text Generation
on ToTTo
Augmenting Knowledge Graphs for Better Link Prediction
Experiments on legacy benchmarks and a new large benchmark, DWD, show that augmenting the knowledge graph with quantities and years is beneficial for predicting both entities and numbers, as KGA outperforms the vanilla models and other relevant baselines.
Evaluating Machine Common Sense via Cloze Testing
Language models (LMs) show state of the art performance for common sense (CS) question answering, but whether this ability implies a human-level mastery of CS remains an open question.
Table-based Fact Verification with Salience-aware Learning
From one perspective, our system conducts masked salient token prediction to enhance the model for alignment and reasoning between the table and the statement.
Ranked #8 on
Table-based Fact Verification
on TabFact
User-friendly Comparison of Similarity Algorithms on Wikidata
While the similarity between two concept words has been evaluated and studied for decades, much less attention has been devoted to algorithms that can compute the similarity of nodes in very large knowledge graphs, like Wikidata.
Creating and Querying Personalized Versions of Wikidata on a Laptop
Application developers today have three choices for exploiting the knowledge present in Wikidata: they can download the Wikidata dumps in JSON or RDF format, they can use the Wikidata API to get data about individual entities, or they can use the Wikidata SPARQL endpoint.
A Study of the Quality of Wikidata
Wikidata has been increasingly adopted by many communities for a wide variety of applications, which demand high-quality knowledge to deliver successful results.
Retrieving Complex Tables with Multi-Granular Graph Representation Learning
The task of natural language table retrieval (NLTR) seeks to retrieve semantically relevant tables based on natural language queries.
PaCo: Preconditions Attributed to Commonsense Knowledge
To address this gap, we propose a novel challenge of reasoning with circumstantial preconditions.
Dimensions of Commonsense Knowledge
Recently, the focus has been on large text-based sources, which facilitate easier integration with neural (language) models and application to textual tasks, typically at the expense of the semantics of the sources and their harmonization.
CSKG: The CommonSense Knowledge Graph
Sources of commonsense knowledge support applications in natural language understanding, computer vision, and knowledge graphs.
Commonsense Knowledge in Wikidata
Our experiments reveal that: 1) albeit Wikidata-CS represents a small portion of Wikidata, it is an indicator that Wikidata contains relevant commonsense knowledge, which can be mapped to 15 ConceptNet relations; 2) the overlap between Wikidata-CS and other commonsense sources is low, motivating the value of knowledge integration; 3) Wikidata-CS has been evolving over time at a slightly slower rate compared to the overall Wikidata, indicating a possible lack of focus on commonsense knowledge.
Consolidating Commonsense Knowledge
Commonsense reasoning is an important aspect of building robust AI systems and is receiving significant attention in the natural language understanding, computer vision, and knowledge graphs communities.
KGTK: A Toolkit for Large Knowledge Graph Manipulation and Analysis
Knowledge graphs (KGs) have become the preferred technology for representing, sharing and adding knowledge to modern AI applications.
Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering
In this paper, we augment a general commonsense QA framework with a knowledgeable path generator.
FlagIt: A System for Minimally Supervised Human Trafficking Indicator Mining
In this paper, we describe and study the indicator mining problem in the online sex advertising domain.
Using Contexts and Constraints for Improved Geotagging of Human Trafficking Webpages
Extracting geographical tags from webpages is a well-motivated application in many domains.
Supervised Typing of Big Graphs using Semantic Embeddings
We propose a supervised algorithm for generating type embeddings in the same semantic vector space as a given set of entity embeddings.
Information Extraction in Illicit Domains
Extracting useful entities and attribute values from illicit domains such as human trafficking is a challenging problem with the potential for widespread social impact.
Learning the Semantics of Structured Data Sources
This model represents the semantics of the new source in terms of the concepts and relationships defined by the domain ontology.
Design of a GIS-based Assistant Software Agent for the Incident Commander to Coordinate Emergency Response Operations
Problem: This paper addresses the design of an intelligent software system for the IC (incident commander) of a team in order to coordinate actions of agents (field units or robots) in the domain of emergency/crisis response operations.
