This paper presents contributions in two directions: first we propose a new system for Frame Identification (FI), based on pre-trained text encoders trained discriminatively and graphs embedding, producing state of the art performance and, second, we take in consideration all the extremely different procedures used to evaluate systems for this task performing a complete evaluation over two benchmarks and all possible splits and cleaning procedures used in the FI literature.
Tamburini Fabio (2022). Combining ELECTRA and Adaptive Graph Encoding for Frame Identification. Paris : European Language Resources Association.
Combining ELECTRA and Adaptive Graph Encoding for Frame Identification
Tamburini Fabio
2022
Abstract
This paper presents contributions in two directions: first we propose a new system for Frame Identification (FI), based on pre-trained text encoders trained discriminatively and graphs embedding, producing state of the art performance and, second, we take in consideration all the extremely different procedures used to evaluate systems for this task performing a complete evaluation over two benchmarks and all possible splits and cleaning procedures used in the FI literature.File in questo prodotto:
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2022.lrec-1.178.pdf
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