@inproceedings{rashidian-brunswicker-2025-merging,
title = "Merging Two Grammar Worlds: Exploring the Relationship between {U}niversal {D}ependencies and Signal Temporal Logic",
author = "Rashidian, Christopher and
Brunswicker, Sabine",
editor = "Inui, Kentaro and
Sakti, Sakriani and
Wang, Haofen and
Wong, Derek F. and
Bhattacharyya, Pushpak and
Banerjee, Biplab and
Ekbal, Asif and
Chakraborty, Tanmoy and
Singh, Dhirendra Pratap",
booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
month = dec,
year = "2025",
address = "Mumbai, India",
publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-ijcnlp.116/",
pages = "1852--1866",
ISBN = "979-8-89176-303-6",
abstract = "Translating natural language requirements into Signal Temporal Logic (STL) is essential for safety-critical systems but requires mathematical expertise. We propose a translational grammar mapping Universal Dependencies (UD) structures to STL Operators through 17 theoretically-motivated patterns, evaluated on the NL2TL benchmarking dataset of 7,002 expert-annotated sentence-STL pairs, and an additional cross-domain analysis. We built a parser guided by this grammar to explore the formal deterministic relationship between UDR Compositions and STL Operators, achieving {\textasciitilde}99{\%} sentence coverage, {\textasciitilde}54{\%} exact matches (and {\textasciitilde}97{\%} similarity). Sentence-level regression analyses predict STL statements and STL Operator classes, considering the co-occurance of UDR substructures (UDR components) with an accuracy of more than {\textasciitilde}74{\%} and {\textasciitilde}81{\%}, respectively. They uncover a new logical grammatical link between temporal NL and formal logic, that is conditioned by the sentence-level context, and provide insights into how linguistic theory unfolds in practice through temporal linguistic expressions."
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<abstract>Translating natural language requirements into Signal Temporal Logic (STL) is essential for safety-critical systems but requires mathematical expertise. We propose a translational grammar mapping Universal Dependencies (UD) structures to STL Operators through 17 theoretically-motivated patterns, evaluated on the NL2TL benchmarking dataset of 7,002 expert-annotated sentence-STL pairs, and an additional cross-domain analysis. We built a parser guided by this grammar to explore the formal deterministic relationship between UDR Compositions and STL Operators, achieving ~99% sentence coverage, ~54% exact matches (and ~97% similarity). Sentence-level regression analyses predict STL statements and STL Operator classes, considering the co-occurance of UDR substructures (UDR components) with an accuracy of more than ~74% and ~81%, respectively. They uncover a new logical grammatical link between temporal NL and formal logic, that is conditioned by the sentence-level context, and provide insights into how linguistic theory unfolds in practice through temporal linguistic expressions.</abstract>
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%0 Conference Proceedings
%T Merging Two Grammar Worlds: Exploring the Relationship between Universal Dependencies and Signal Temporal Logic
%A Rashidian, Christopher
%A Brunswicker, Sabine
%Y Inui, Kentaro
%Y Sakti, Sakriani
%Y Wang, Haofen
%Y Wong, Derek F.
%Y Bhattacharyya, Pushpak
%Y Banerjee, Biplab
%Y Ekbal, Asif
%Y Chakraborty, Tanmoy
%Y Singh, Dhirendra Pratap
%S Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
%D 2025
%8 December
%I The Asian Federation of Natural Language Processing and The Association for Computational Linguistics
%C Mumbai, India
%@ 979-8-89176-303-6
%F rashidian-brunswicker-2025-merging
%X Translating natural language requirements into Signal Temporal Logic (STL) is essential for safety-critical systems but requires mathematical expertise. We propose a translational grammar mapping Universal Dependencies (UD) structures to STL Operators through 17 theoretically-motivated patterns, evaluated on the NL2TL benchmarking dataset of 7,002 expert-annotated sentence-STL pairs, and an additional cross-domain analysis. We built a parser guided by this grammar to explore the formal deterministic relationship between UDR Compositions and STL Operators, achieving ~99% sentence coverage, ~54% exact matches (and ~97% similarity). Sentence-level regression analyses predict STL statements and STL Operator classes, considering the co-occurance of UDR substructures (UDR components) with an accuracy of more than ~74% and ~81%, respectively. They uncover a new logical grammatical link between temporal NL and formal logic, that is conditioned by the sentence-level context, and provide insights into how linguistic theory unfolds in practice through temporal linguistic expressions.
%U https://aclanthology.org/2025.findings-ijcnlp.116/
%P 1852-1866
Markdown (Informal)
[Merging Two Grammar Worlds: Exploring the Relationship between Universal Dependencies and Signal Temporal Logic](https://aclanthology.org/2025.findings-ijcnlp.116/) (Rashidian & Brunswicker, Findings 2025)
ACL