Špela Vintar

Špela Vintar, Jan Jona Javoršek

Human word associations are a well-known method of gaining insight into the internal mental lexicon, but the responses spontaneously offered by human participants to word cues are not always predictable as they may be influenced by personal experience, emotions or individual cognitive styles. The ability to form associative links between seemingly unrelated concepts can be the driving mechanisms of creativity. We perform a comparison of the associative behaviour of humans compared to large language models. More specifically, we explore associations to emotionally loaded words and try to determine whether large language models generate associations in a similar way to humans. We find that the overlap between humans and LLMs is moderate, but also that the associations of LLMs tend to amplify the underlying emotional load of the stimulus, and that they tend to be more predictable and less creative than human ones.

Larisa Grčić Simeunović, Matej Martinc, Špela Vintar

We present an experiment in extracting adjectives which express a specific semantic relation using word embeddings. The results of the experiment are then thoroughly analysed and categorised into groups of adjectives exhibiting formal or semantic similarity. The experiment and analysis are performed for English and Croatian in the domain of karstology using data sets and methods developed in the TermFrame project. The main original contributions of the article are twofold: firstly, proposing a new and promising method of extracting semantically related words relevant for terminology, and secondly, providing a detailed evaluation of the output so that we gain a better understanding of the domain-specific semantic structures on the one hand and the types of similarities extracted by word embeddings on the other.