CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge

@inproceedings{Wang2021CogNetBL,
  title={CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge},
  author={Chenhao Wang and Yubo Chen and Zhipeng Xue and Yang Zhou and Jun Zhao},
  booktitle={AAAI},
  year={2021}
}
In this paper, we present CogNet, a knowledge base (KB) dedicated to integrating three types of knowledge: (1) linguistic knowledge from FrameNet, which schematically describes situations, objects and events. (2) world knowledge from YAGO, Freebase, DBpedia and Wikidata, which provides explicit knowledge about specific instances. (3) commonsense knowledge from ConceptNet, which describes implicit general facts. To model these different types of knowledge consistently, we introduce a three-level… 

Figures from this paper

CogIE: An Information Extraction Toolkit for Bridging Texts and CogNet

TLDR
This paper proposes an information extraction toolkit, called CogIE, which is a bridge connecting raw texts and CogNet, and releases an open-access online system to visually extract information from texts.

CogKGE: A Knowledge Graph Embedding Toolkit and Benchmark for Representing Multi-source and Heterogeneous Knowledge

TLDR
This paper proposes CogKGE, a knowledge graph embedding (KGE) toolkit, which aims to represent multi-source and heterogeneous knowledge and provides pre-trained embedders to discover new facts, cluster entities and check facts.

Towards Natural Language Interfaces for Data Visualization: A Survey

TLDR
This article conducts a comprehensive review of the existing V-NLIs and develops categorical dimensions based on a classic information visualization pipeline with the extension of a V-NLI layer.

References

SHOWING 1-10 OF 14 REFERENCES

Framester: A Wide Coverage Linguistic Linked Data Hub

TLDR
This work created a novel resource, Framester, which acts as a hub between FrameNet, WordNet, VerbNet, BabelNet, DBpedia, Yago, DOLCE-Zero, as well as other resources, and applies a rigorous formal treatment for Fillmore's frame semantics, enabling full-fledged OWL querying and reasoning on a large frame-based knowledge graph.

ConceptNet 5.5: An Open Multilingual Graph of General Knowledge

TLDR
A new version of the linked open data resource ConceptNet is presented that is particularly well suited to be used with modern NLP techniques such as word embeddings, with state-of-the-art results on intrinsic evaluations of word relatedness that translate into improvements on applications of word vectors, including solving SAT-style analogies.

Yago: A Core of Semantic Knowledge Unifying WordNet and Wikipedia

TLDR
YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts, which includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as hasWonPrize).

DBpedia - A large-scale, multilingual knowledge base extracted from Wikipedia

TLDR
An overview of the DBpedia community project is given, including its architecture, technical implementation, maintenance, internationalisation, usage statistics and applications, including DBpedia one of the central interlinking hubs in the Linked Open Data (LOD) cloud.

FrameBase: Representing N-Ary Relations Using Semantic Frames

TLDR
FrameBase is presented, a wide-coverage knowledge-base schema that uses linguistic frames to seamlessly represent and query n-ary relations from other knowledge bases, at different levels of granularity connected by logical entailment.

ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning

TLDR
Experimental results demonstrate that multitask models that incorporate the hierarchical structure of if-then relation types lead to more accurate inference compared to models trained in isolation, as measured by both automatic and human evaluation.

The Berkeley FrameNet Project

TLDR
This report will present the project's goals and workflow, and information about the computational tools that have been adapted or created in-house for this work.

PreMOn: a Lemon Extension for Exposing Predicate Models as Linked Data

We introduce PreMOn (predicate model for ontologies), a linguistic resource for exposing predicate models (PropBank, NomBank, VerbNet, and FrameNet) and mappings between them (e.g, SemLink) as Linked

Renewing and Revising SemLink

This research describes SemLink, a comprehensive resource for Natural Language Processing that maps and unifies several highquality lexical resources: PropBank, VerbNet, FrameNet, and the recently

Predicate Matrix: extending SemLink through WordNet mappings

TLDR
This paper presents the Predicate Matrix v1.1, a new lexical resource resulting from the integration of multiple sources of predicate information including FrameNet, VerbNet, PropBank and WordNet, which largely extends the current coverage of SemLink and the previous version of the Predicates Matrix.