Know-Center at SemEval-2016 Task 5: Using Word Vectors with Typed Dependencies for Opinion Target Expression Extraction

Stefan Falk, Andi Rexha, Roman Kern

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


This paper describes our participation in SemEval-2016 Task 5 for Subtask 1, Slot 2. The challenge demands to find domain specific target expressions on sentence level that refer to reviewed entities. The detection of target words is achieved by using word vectors and their grammatical dependency relationships to classify each word in a sentence into target or non-target. A heuristic based function then expands the classified target words to the whole target phrase. Our system achieved an F1 score of 56.816% for this task. © 2016 Association for Computational Linguistics.
Original languageGerman
Title of host publicationProceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
Publication statusPublished - 2016
Event10th International Workshop on Semantic Evaluation: SemEval 2016 - San Diego, United States
Duration: 16 Jun 201617 Jun 2016


Conference10th International Workshop on Semantic Evaluation
Country/TerritoryUnited States
CitySan Diego

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