A graph-based analysis of semantic types and coercion in contextualized word embeddings
Researchers propose a graph-based framework to measure how contextualized embeddings capture semantic type information, a foundational problem in NLP. By analyzing neighborhood distributions in BERT and sense-enhanced embeddings, the work demonstrates that enriched semantic representations better distinguish between type-matching and coercion contexts. This advances interpretability of how modern language models encode compositional meaning, with implications for downstream tasks requiring fine-grained semantic reasoning.
Modelwire context
ExplainerThe paper's core contribution is operationalizing semantic type distinction through neighborhood graph analysis rather than relying on task performance as a proxy. Prior work assumed embeddings captured type information if downstream tasks improved; this work directly measures whether the embedding space itself encodes the semantic structures needed for compositional reasoning.
This connects to the NLG evaluation paper from May 22nd, which highlighted the field's shift from informal critique to rigorous experimental validation. Both stories reflect a broader pattern in NLP: moving from black-box task metrics to interpretable, measurable properties of the models themselves. The graph-based analysis here is part of that same methodological maturation. Where that piece worried about evaluation rigor in production systems, this work addresses the upstream problem of understanding what representations actually encode before we deploy them.
If follow-up work applies this graph-based framework to probe other linguistic phenomena (agreement, scope, argument structure) and shows consistent gaps between BERT and sense-enhanced models, that confirms the method generalizes beyond type coercion. If the framework remains specific to this one phenomenon, it's a useful diagnostic tool but not a broader interpretability approach.
Coverage we drew on
- NLG Evaluation: Past, Present, Future · arXiv cs.CL
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