For each of the following sample we assume:



A sample from linked-extractions.tsv dataset:

1) Kemnitz is a municipality in the Ostvorpommern district

partOf(Kemnitz, Ostvorpommern)

2) Shua is a village in the Astara Rayon of Azerbaijan

partOf(Shua, Astara Rayon) ^ Village(Shua)

3) Mie Prefecture forms the eastern part of the Kii Peninsula

partOf(Mie Prefecture, Kii Peninsula)

4) Mumps vaccine is a part of the MMR vaccine

partOf(Mumps vaccine, MMR vaccine)

5) Euramerica was a part of Laurasia

 partOf(Euramerica, Laurasia) ??

6) Galactose is part of lactose

partOf(Galactose, lactose)

Dihydroergotamine is used to treat migraine headaches


What to do?

  1. Learn (identify) and classify the semantic relations between the Linked Entities, with emphasis on Partonomy detection. then (2nd goal)
  2. Generalize (subsume) an Entity “instance” in a relation to its (ontological) concept. e.g. partOf(engine123, Car) ==> partOf(Engine, Vehicle)