Summary of Human and Automatic Interpretation Of Romanian Noun Compounds, by Ioana Marinescu and Christiane Fellbaum
Human and Automatic Interpretation of Romanian Noun Compounds
by Ioana Marinescu, Christiane Fellbaum
First submitted to arxiv on: 11 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper tackles the problem of determining the intended meanings of noun compounds in Romanian, such as “shoe sale” and “fire sale”, which can have different meanings depending on context. Previous approaches relied on inventories of semantic relations between compound members. The authors propose a new set of relations and test it using human annotators and a neural network classifier. The results show that the neural net’s predictions align with human judgments, even in cases where human agreement is low. The study also reveals that the most frequently selected relation was not one of the sixteen labeled semantic relations, highlighting the need for a more comprehensive relation inventory. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In simple terms, this paper helps computers better understand phrases like “shoe sale” and “fire sale”. These phrases have different meanings depending on the situation. Previously, researchers used lists of relationships between words to figure out what these phrases mean. This new study tests a different approach using human helpers and computer models. The results show that the computer model’s predictions match what humans think the phrases mean, even when there is disagreement. Interestingly, the most common answer was not one that experts had previously identified. |
Keywords
» Artificial intelligence » Neural network
