Domagoj Alagić


2017

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A Preliminary Study of Croatian Lexical Substitution
Domagoj Alagić | Jan Šnajder
Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing

Lexical substitution is a task of determining a meaning-preserving replacement for a word in context. We report on a preliminary study of this task for the Croatian language on a small-scale lexical sample dataset, manually annotated using three different annotation schemes. We compare the annotations, analyze the inter-annotator agreement, and observe a number of interesting language specific details in the obtained lexical substitutes. Furthermore, we apply a recently-proposed, dependency-based lexical substitution model to our dataset. The model achieves a P@3 score of 0.35, which indicates the difficulty of the task.

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Debunking Sentiment Lexicons: A Case of Domain-Specific Sentiment Classification for Croatian
Paula Gombar | Zoran Medić | Domagoj Alagić | Jan Šnajder
Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing

Sentiment lexicons are widely used as an intuitive and inexpensive way of tackling sentiment classification, often within a simple lexicon word-counting approach or as part of a supervised model. However, it is an open question whether these approaches can compete with supervised models that use only word-representation features. We address this question in the context of domain-specific sentiment classification for Croatian. We experiment with the graph-based acquisition of sentiment lexicons, analyze their quality, and investigate how effectively they can be used in sentiment classification. Our results indicate that, even with as few as 500 labeled instances, a supervised model substantially outperforms a word-counting model. We also observe that adding lexicon-based features does not significantly improve supervised sentiment classification.

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TakeLab at SemEval-2017 Task 6: #RankingHumorIn4Pages
Marin Kukovačec | Juraj Malenica | Ivan Mršić | Antonio Šajatović | Domagoj Alagić | Jan Šnajder
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper describes our system for humor ranking in tweets within the SemEval 2017 Task 6: #HashtagWars (6A and 6B). For both subtasks, we use an off-the-shelf gradient boosting model built on a rich set of features, handcrafted to provide the model with the external knowledge needed to better predict the humor in the text. The features capture various cultural references and specific humor patterns. Our system ranked 2nd (officially 7th) among 10 submissions on the Subtask A and 2nd among 9 submissions on the Subtask B.

2016

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Cro36WSD: A Lexical Sample for Croatian Word Sense Disambiguation
Domagoj Alagić | Jan Šnajder
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

We introduce Cro36WSD, a freely-available medium-sized lexical sample for Croatian word sense disambiguation (WSD).Cro36WSD comprises 36 words: 12 adjectives, 12 nouns, and 12 verbs, balanced across both frequency bands and polysemy levels. We adopt the multi-label annotation scheme in the hope of lessening the drawbacks of discrete sense inventories and obtaining more realistic annotations from human experts. Sense-annotated data is collected through multiple annotation rounds to ensure high-quality annotations: with a 115 person-hours effort we reached an inter-annotator agreement score of 0.877. We analyze the obtained data and perform a correlation analysis between several relevant variables, including word frequency, number of senses, sense distribution skewness, average annotation time, and the observed inter-annotator agreement (IAA). Using the obtained data, we compile multi- and single-labeled dataset variants using different label aggregation schemes. Finally, we evaluate three different baseline WSD models on both dataset variants and report on the insights gained. We make both dataset variants freely available.

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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)

2015

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Experiments on Active Learning for Croatian Word Sense Disambiguation
Domagoj Alagić | Jan Šnajder
The 5th Workshop on Balto-Slavic Natural Language Processing