Papers with context-aware neural network model

2 papers
Context-Aware Neural Model for Temporal Information Extraction (P18-1)

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Challenge: Existing temporal information extraction systems rely on statistical learning with feature-engineered task-specific models.
Approach: They propose a context-aware neural network model for temporal information extraction using a global context layer.
Outcome: The proposed model outperforms existing models in terms of performance and performance . it is the first model to use NTM-like architecture to process the information from global context in discourse-scale natural text processing.
Automated Phonological Transcription of Akkadian Cuneiform Text (2020.lrec-1)

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Challenge: Akkadian was an east-semitic language spoken in ancient Mesopotamia . cuneiform text does not mark the inflection for logograms, so the inflected form needs to be inferred from the sentence context.
Approach: They propose to automate phonological transcription of the transliterated Akkadian corpora . transcription is normalized according to the grammatical description of a given dialect . they find that cuneiform text does not mark the inflection for logograms .
Outcome: The proposed transcriptions show the Akkadian renderings for Sumerian logograms, while the logogram transcription is more challenging.

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