@inproceedings{carp-2026-harapalb,
title = "harapalb at {S}em{E}val-2026 Task 4: Multi-Signal Neuro-Symbolic Ensembles for Narrative Similarity",
author = "Carp, Andrei Tiberiu",
editor = "Kochmar, Ekaterina and
Ghosh, Debanjan and
North, Kai and
Komachi, Mamoru",
booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.semeval-1.283/",
pages = "2238--2244",
ISBN = "979-8-89176-414-9",
abstract = "This paper presents a neuro-symbolic ensemble for determining narrative similarity by moving beyond surface-level text matching toward structural and causal alignment. The architecture fuses three primary signals: action-focused neural embeddings that isolate event trajectories , a symbolic Structural Survival Ratio (SSR) that measures the preservation of discrete event tuples via dependency parsing , and high-level structural comparisons conducted by the gpt-5-mini model. Evaluated on the SemEval-2026 Task 4 test set, the integrated ensemble achieved an accuracy of 68.25{\%}."
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%0 Conference Proceedings
%T harapalb at SemEval-2026 Task 4: Multi-Signal Neuro-Symbolic Ensembles for Narrative Similarity
%A Carp, Andrei Tiberiu
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F carp-2026-harapalb
%X This paper presents a neuro-symbolic ensemble for determining narrative similarity by moving beyond surface-level text matching toward structural and causal alignment. The architecture fuses three primary signals: action-focused neural embeddings that isolate event trajectories , a symbolic Structural Survival Ratio (SSR) that measures the preservation of discrete event tuples via dependency parsing , and high-level structural comparisons conducted by the gpt-5-mini model. Evaluated on the SemEval-2026 Task 4 test set, the integrated ensemble achieved an accuracy of 68.25%.
%U https://aclanthology.org/2026.semeval-1.283/
%P 2238-2244
Markdown (Informal)
[harapalb at SemEval-2026 Task 4: Multi-Signal Neuro-Symbolic Ensembles for Narrative Similarity](https://aclanthology.org/2026.semeval-1.283/) (Carp, SemEval 2026)
ACL