Ivan Sekulić


2016

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VerbCROcean: A Repository of Fine-Grained Semantic Verb Relations for Croatian
Ivan Sekulić | Jan Šnajder
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In this paper we describe VerbCROcean, a broad-coverage repository of fine-grained semantic relations between Croatian verbs. Adopting the methodology of Chklovski and Pantel (2004) used for acquiring the English VerbOcean, we first acquire semantically related verb pairs from a web corpus hrWaC by relying on distributional similarity of subject-verb-object paths in the dependency trees. We then classify the semantic relations between each pair of verbs as similarity, intensity, antonymy, or happens-before, using a number of manually-constructed lexico-syntatic patterns. We evaluate the quality of the resulting resource on a manually annotated sample of 1000 semantic verb relations. The evaluation revealed that the predictions are most accurate for the similarity relation, and least accurate for the intensity relation. We make available two variants of VerbCROcean: a coverage-oriented version, containing about 36k verb pairs at a precision of 41%, and a precision-oriented version containing about 5k verb pairs, at a precision of 56%.

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TakeLab at SemEval-2016 Task 6: Stance Classification in Tweets Using a Genetic Algorithm Based Ensemble
Martin Tutek | Ivan Sekulić | Paula Gombar | Ivan Paljak | Filip Čulinović | Filip Boltužić | Mladen Karan | Domagoj Alagić | Jan Šnajder
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)