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The AMAR mechanism: nominal expressions in the Bantu languages are shaped by apposition and reintegration.
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In: ISSN: 0024-3949 ; EISSN: 1613-396X ; Linguistics ; https://halshs.archives-ouvertes.fr/halshs-03433014 ; Linguistics, De Gruyter, In press, ⟨10.1515/ling-2020-0132⟩ (2022)
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Wh-interrogatives in ancient Greek ; Wh-interrogatives in ancient Greek: Disentangling focus- and wh-movement
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In: ISSN: 0039-3193 ; EISSN: 1467-9582 ; Studia Linguistica ; https://hal.archives-ouvertes.fr/hal-03579191 ; Studia Linguistica, Wiley-Blackwell, In press (2022)
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La notion d’applicatif en chinois mandarin : du dérivationnel au compositionnel
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In: In D.-T. Do-Hurinville, D. Petit, H.-L. Dao & A. Rialland (éds), L’applicatif dans les langues. Regard typologique. Éditions de la Société de Linguistique de Paris. ; https://hal.archives-ouvertes.fr/hal-03551904 ; In D.-T. Do-Hurinville, D. Petit, H.-L. Dao & A. Rialland (éds), L’applicatif dans les langues. Regard typologique. Éditions de la Société de Linguistique de Paris., A paraître (2022)
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Quality and Efficiency of Manual Annotation: Data from the Pre-annotation Bias Experiment (part of the PDT-C 2.0 project)
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Interpretation of wh-copying constructions in a non-wh-copying language ...
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LINGUISTIC ANALYSIS OF SIMPLE SENTENCE CONSTRUCTION IN UZBEK AND FRENCH ...
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LINGUISTIC ANALYSIS OF SIMPLE SENTENCE CONSTRUCTION IN UZBEK AND FRENCH ...
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A Quantitative Approach to Microvariation: Negative Marking in Central Romance
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In: Languages; Volume 7; Issue 2; Pages: 87 (2022)
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Effect of Lexical-Semantic Cues during Real-Time Sentence Processing in Aphasia
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In: Brain Sciences; Volume 12; Issue 3; Pages: 312 (2022)
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Lexical Category and Downstep in Japanese
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In: Languages; Volume 7; Issue 1; Pages: 25 (2022)
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A Quantum Language-Inspired Tree Structural Text Representation for Semantic Analysis
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In: Mathematics; Volume 10; Issue 6; Pages: 914 (2022)
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Abstract:
Text representation is an important topic in the field of natural language processing, which can effectively transfer knowledge to downstream tasks. To extract effective semantic information from text with unsupervised methods, this paper proposes a quantum language-inspired tree structural text representation model to study the correlations between words with variable distance for semantic analysis. Combining the different semantic contributions of associated words in different syntax trees, a syntax tree-based attention mechanism is established to highlight the semantic contributions of non-adjacent associated words and weaken the semantic weight of adjacent non-associated words. Moreover, the tree-based attention mechanism includes not only the overall information of entangled words in the dictionary but also the local grammatical structure of word combinations in different sentences. Experimental results on semantic textual similarity tasks show that the proposed method obtains significant performances over the state-of-the-art sentence embeddings.
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Keyword:
attention mechanism; natural language processing; quantum language-inspired; semantic analysis; syntax tree
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URL: https://doi.org/10.3390/math10060914
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Grammatical Gender Disambiguates Syntactically Similar Nouns
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In: Entropy; Volume 24; Issue 4; Pages: 520 (2022)
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The Spell-Out of Non-Heads in Spanish Compounds: A Nanosyntactic Approach
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In: Languages; Volume 7; Issue 2; Pages: 105 (2022)
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On the Nature of Syntactic Satiation
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In: Languages; Volume 7; Issue 1; Pages: 38 (2022)
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Why Is Inflectional Morphology Difficult to Borrow?—Distributing and Lexicalizing Plural Allomorphy in Pennsylvania Dutch
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In: Languages; Volume 7; Issue 2; Pages: 86 (2022)
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Semantic Feature Extraction Using SBERT for Dementia Detection
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In: Brain Sciences; Volume 12; Issue 2; Pages: 270 (2022)
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