Semantic Representation of Relative Clauses in Lexicalized Abstract Meaning Representation

2026-04-12 · Source: Paper Index on ACL Anthology · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics · Depth: Expert, quick

Summary

This study examines the semantic parsing of Portuguese relative clauses within two meaning representation frameworks: Abstract Meaning Representation (AMR) and Lexicalized Meaning Representation (LMR). Both frameworks model relative clauses as noun modifiers. However, the analysis reveals that AMR does not differentiate between restrictive and appositive relative clauses, a distinction considered grammatically significant. The authors advocate for the explicit encoding of this grammatical difference within semantic representations. The research utilizes annotated translations of *The Little Prince* (Saint-Exupéry, 1943) in both Brazilian and European Portuguese, specifically identifying and discussing issues found in the Brazilian Portuguese AMR annotations.

Key takeaway

For research scientists working on semantic parsing of Romance languages, you should consider the explicit encoding of restrictive versus appositive relative clauses in your meaning representations. Failing to distinguish these can lead to semantic ambiguities and misinterpretations, particularly when using frameworks like AMR for languages such as Portuguese.

Key insights

AMR lacks a crucial distinction between restrictive and appositive relative clauses in Portuguese.

Principles

• Grammatical distinctions require explicit semantic encoding.
• Relative clauses function as noun modifiers.

Method

The study analyzes annotated translations of *The Little Prince* in Brazilian and European Portuguese to identify semantic parsing issues in AMR and LMR.

In practice

• Review AMR annotations for relative clause distinctions.
• Develop explicit encoding for appositive clauses.

Topics

• Semantic Parsing
• Relative Clauses
• Abstract Meaning Representation
• Lexicalized Meaning Representation
• Portuguese Linguistics

Best for: Research Scientist, AI Scientist, NLP Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Paper Index on ACL Anthology.