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Label unstructured data using Enterprise Knowledge Graphs 3

Target Sense Verification


Looking for concepts behind words

Typical Entity Linking task statement
Disambiguation with Enterprise Knowledge Graphs

Running example — “Jaguars”

[{1: “The jaguar’s present range extends from Southwestern United States and Mexico in North America, across much of Central America, and south to Paraguay and northern Argentina in South America.”},
{2: “Overall, the jaguar is the largest native cat species of the New World and the third largest in the world.”},
{3: “Given its historical distribution, the jaguar has featured prominently in the mythology of numerous indigenous American cultures, including those of the Maya and Aztec.”},
{4: “The jaguar is a compact and well-muscled animal.”},
{5: “Melanistic jaguars are informally known as black panthers, but as with all forms of polymorphism they do not form a separate species.”},
{6: “The jaguar uses scrape marks, urine, and feces to mark its territory.”},
{7: “The word ‘jaguar’ is thought to derive from the Tupian word yaguara, meaning ‘beast of prey’.”},{8: “Jaguar’s business was founded as the Swallow Sidecar Company in 1922, originally making motorcycle sidecars before developing bodies for passenger cars.”},
{9: “In 1990 Ford acquired Jaguar Cars and it remained in their ownership, joined in 2000 by Land Rover, till 2008.”},
{10: “Two of the proudest moments in Jaguar’s long history in motor sport involved winning the Le Mans 24 hours race, firstly in 1951 and again in 1953.”},
{11: “He therefore accepted BMC’s offer to merge with Jaguar to form British Motor (Holdings) Limited.”},
{12: “The Jaguar E-Pace is a compact SUV, officially revealed on 13 July 2017.”}]

Limitations of the previous approaches

Target Sense Verification



PhD in applied math and CS. Semantic Web, NLP, Information Extraction, Machine Learning and friends