BLM-CausI (Blackbird Language Matrices Causative/Inchoative verb alternations in Italian)

Description

BLM-CausI is a Change-of-state (CoS) alternation dataset for testing lexical semantic properties of verbs, their ability to enter or not a causative alternation. CoS represents the causative/inchoative alternation, where the object of the transitive verb bears the same semantic role (Patient) as the subject of the intransitive verb (L'artista ha aperto la finestra/La finestra si è aperta `The artist opened the window'/`The window opened'). The transitive form of the verb has a causative meaning. 

Blackbird Language Matrices (BLMs) are multiple-choice problems, where the input is a sequence of sentences built using specific generating rules, and the answer set consists of a correct answer that continues the input sequence, and several incorrect contrastive options, built by violating the underlying generating rules of the sentences. In a  BLM matrix, all sentences share the targeted linguistic phenomenon (in this case verb alternations), but differ in other aspects relevant for the phenomenon in question.   

BLM datasets also have a lexical variation dimension, to explore the impact of lexical variation on detecting relevant structures: type I – minimal lexical variation for sentences within an instance, type II – one word difference across the sentences within an instance, type III – maximal lexical variation within an instance. 

The data comes grouped by lexical variation (i.e. type I/II/III) and each subset is split into train/test. Each split contains 2140 training and 240 testing instances.

Reference

If you use this dataset,please cite the following publication:

Nastase, Vivi& Samo, Giuseppe & Jiang, Chunyang & Merlo, Paola. (2024). Exploring Italian sentence embeddings properties through multi-tasking. DOI: 10.48550/arXiv.2409.06622.