D5
Databases and Information Systems

Overview

This page is dedicated to the project on Informative Negative Knowledge about Everyday Concepts.

Publications

  • UnCommonSense: Informative Negative Knowledge about Everyday Concepts. CIKM'22 (to appear)

Datasets

Download 6.2million negations about 8k everyday concepts.
Details: concepts source, methodology in strict-rank mode and with provenances.

Samples:

 


{
    "subject": "gorilla",
    "predicate": "HasProperty",
    "object": "territorial",
    "tail_phrase": "be territorial",
    "score": 0.23, 
    "strict_siblings": 
        [
            {
                "wild animal": ["tiger", "lion", "monkey", "chimpanzee"]
            }, 
            
            {
                "species": ["wombat", "tarsier", "gibbon"]
            }
        ]
}

{
    "subject": "tabbouleh",
    "predicate": "ReceivesAction",
    "object": "baked",
    "tail_phrase": "be baked"
    "score": 0.17,
    "strict_siblings": 
        [
            {
                "food": ["loaf", "samosa", "flatbread"]
            }, 
            
            {
                "side dish": ["casserole", "pasta"]
            }
        ]
}

 

Download 6.3million negations about 8k everyday concepts.
Details: concepts source, methodology in relaxed-rank mode.

Samples:

 


{
    "subject": "elephant",
    "predicate": "CapableOf",
    "object": "catch prey",
    "score": 0.23, 
    "strict_siblings": 
        [
            "tiger"
        ], 
    "relaxed_siblings":
        [
            {
                "subject": "cheetah", 
                "predicate": "CapableOf", 
                "object": "catch their prey"
            }, 
            {
                "subject": "lion",
                "predicate": "CapableOf",
                "object": "eat their prey"
            }, 
            {
                "subject": "crocodile",
                "predicate": "CapableOf",
                "object": "eat their prey"
            },
            {
                "subject": "bear",
                "predicate": "CapableOf",
                "object": "attack prey"
            }
        ]
}

 

Datasets produced from external methods (refer to CIKM'22 paper for details):

NegatER-theta, NegatER-nabla (part1), NegatER-nabla (part2), Quasimodo-neg, GPT-3-neg.