mlsanityData to 14 Oct 2026

'Layer su Layer': Identifying and Disambiguating the Italian NPN Construction in BERT's family

arXiv 2604.03673 ↗First posted 4 Apr 2026cs.CLcited by 0

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Abstract (arXiv)

Interpretability research has highlighted the importance of evaluating Pretrained Language Models (PLMs) and in particular contextual embeddings against explicit linguistic theories to determine what linguistic information they encode. This study focuses on the Italian NPN (noun-preposition-noun) constructional family, challenging some of the theoretical and methodological assumptions underlying previous experimental designs and extending this type of research to a lesser-investigated language. Contextual vector representations are extracted from BERT and used as input to layer-wise probing classifiers, systematically evaluating information encoded across the model's internal layers. The results shed light on the extent to which constructional form and meaning are reflected in contextual embeddings, contributing empirical evidence to the dialogue between constructionist theory and neural language modelling

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 30 references that are in the map. First posted on arXiv 4 Apr 2026.

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13 of 30 references.

References · 13

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  3. 2016Enriching Word Vectors with Subword Informationcited by 1,583
  4. 2019BERT Rediscovers the Classical NLP Pipelinecited by 1,059
  5. 2016Bag of Tricks for Efficient Text Classificationcited by 876
  6. 2020A Primer in BERTology: What we know about how BERT workscited by 815
  7. 2019Designing and Interpreting Probes with Control Taskscited by 640
  8. 2022The Better Your Syntax, the Better Your Semantics? Probing Pretrained Language Models for the English Comparative Correlativecited by 35
  9. 2020CxGBERT: BERT meets Construction Grammarcited by 32
  10. 2025Construction Identification and Disambiguation Using BERT: A Case Study of NPNcited by 4
  11. 2023CALaMo: a Constructionist Assessment of Language Modelscited by 2
  12. 2025LLMs Learn Constructions That Humans Do Not Knowcited by 1
1 more
  1. 2026The Grammar of Transformers: A Systematic Review of Interpretability Research on Syntactic Knowledge in Language Modelscited by 1

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