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Relevant bibliographies by topics / ÌÞesed (The Hebrew word)

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Academic literature on the topic 'ÌÞesed (The Hebrew word)'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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Journal articles on the topic "ÌÞesed (The Hebrew word)"

1

Lavidor, Michal, and Carol Whitney. "Word length effects in Hebrew." Cognitive Brain Research 24, no. 1 (June 2005): 127–32. http://dx.doi.org/10.1016/j.cogbrainres.2005.01.002.

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Schwarzwald, Ora (Rodrigue). "Word Foreignness in Modern Hebrew." Hebrew Studies 39, no. 1 (1998): 115–42. http://dx.doi.org/10.1353/hbr.1998.0000.

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Ryzhik, Michael. "The Lexical Impact of Hebrew in the Judeo-Italian of Medieval and Renaissance Siddur Translations." Journal of Jewish Languages 8, no. 1-2 (November 27, 2020): 7–38. http://dx.doi.org/10.1163/22134638-bja10003.

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Abstract General traits of the Hebrew components of Judeo-Italian Siddur translations are analyzed. The most interesting cases are those where the same Hebrew component is used differently in different contexts: (1) the same Hebrew word remains untranslated in the title and is translated by the Romance lexical unit in the text of the prayer (שבת/sabbeto; כהן/sacerdote); (2) the same Hebrew word in the divine (mystic) sense remains untranslated, while in the secular sense it is translated as the Italian word (צבאות/osti); (3) one Hebrew component lexical unit translates another Hebrew word (אִשִּׁים > קרבנות ;נשך > רבית ;חולק < טענה); (4) one form of the Hebrew word is translated by another form of the same word (עולמות > עולמים). The two latter categories are especially instructive in studying the Hebrew component of spoken and written Judeo-Italian.

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Fuller, David J. "Word Order in Biblical Hebrew Poetry." Journal of Biblical Text Research 44 (April 30, 2019): 216–36. http://dx.doi.org/10.28977/jbtr.2019.4.44.216.

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Goldberg, Yoav, and Michael Elhadad. "Word Segmentation, Unknown-word Resolution, and Morphological Agreement in a Hebrew Parsing System." Computational Linguistics 39, no. 1 (March 2013): 121–60. http://dx.doi.org/10.1162/coli_a_00137.

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We present a constituency parsing system for Modern Hebrew. The system is based on the PCFG-LA parsing method of Petrov et al. 2006 , which is extended in various ways in order to accommodate the specificities of Hebrew as a morphologically rich language with a small treebank. We show that parsing performance can be enhanced by utilizing a language resource external to the treebank, specifically, a lexicon-based morphological analyzer. We present a computational model of interfacing the external lexicon and a treebank-based parser, also in the common case where the lexicon and the treebank follow different annotation schemes. We show that Hebrew word-segmentation and constituency-parsing can be performed jointly using CKY lattice parsing. Performing the tasks jointly is effective, and substantially outperforms a pipeline-based model. We suggest modeling grammatical agreement in a constituency-based parser as a filter mechanism that is orthogonal to the grammar, and present a concrete implementation of the method. Although the constituency parser does not make many agreement mistakes to begin with, the filter mechanism is effective in fixing the agreement mistakes that the parser does make. These contributions extend outside of the scope of Hebrew processing, and are of general applicability to the NLP community. Hebrew is a specific case of a morphologically rich language, and ideas presented in this work are useful also for processing other languages, including English. The lattice-based parsing methodology is useful in any case where the input is uncertain. Extending the lexical coverage of a treebank-derived parser using an external lexicon is relevant for any language with a small treebank.

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Segal, Osnat, Tamar Keren-Portnoy, and Marilyn Vihman. "Infant Recognition of Hebrew Vocalic Word Patterns." Infancy 20, no. 2 (December 16, 2014): 208–36. http://dx.doi.org/10.1111/infa.12072.

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7

Norman, Tal, Tamar Degani, and Orna Peleg. "Transfer of L1 visual word recognition strategies during early stages of L2 learning: Evidence from Hebrew learners whose first language is either Semitic or Indo-European." Second Language Research 32, no. 1 (October 11, 2015): 109–22. http://dx.doi.org/10.1177/0267658315608913.

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The present study examined visual word recognition processes in Hebrew (a Semitic language) among beginning learners whose first language (L1) was either Semitic (Arabic) or Indo-European (e.g. English). To examine if learners, like native Hebrew speakers, exhibit morphological sensitivity to root and word-pattern morphemes, learners made an off-line graded lexical decision task on unfamiliar letter strings. Critically, these letter strings were manipulated to include or exclude familiar Hebrew morphemes. The results demonstrate differential morphological sensitivity as a function of participants’ language background. In particular, Indo-European-L1 learners exhibited increased sensitivity to word-pattern familiarity, with little effect of root familiarity. In contrast, Semitic-L1 learners exhibited non-additive sensitivity to both morphemes. Specifically, letter strings with a familiar root and a familiar word-pattern were the most likely to be judged as real words by this L1-Semitic group, whereas strings with a familiar root in the absence of a familiar word-pattern were the most likely to lead to a non-word decision. These findings show that both groups of learners activate their morphological knowledge in Hebrew in order to process unfamiliar Hebrew words. Critically, the findings further demonstrate transfer of L1 word recognition processes during the initial stages of second language (L2) learning.

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Koriat, Asher, Seth N. Greenberg, and Yona Goldshmid. "The missing-letter effect in Hebrew: Word frequency or word function?" Journal of Experimental Psychology: Learning, Memory, and Cognition 17, no. 1 (January 1991): 66–80. http://dx.doi.org/10.1037/0278-7393.17.1.66.

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Hadari, Atar. "The Word of the Lord to Shylock." European Judaism 51, no. 2 (September 1, 2018): 83–90. http://dx.doi.org/10.3167/ej.2017.510213.

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Dror Abend-David’s Scorned My Nation in its comparative literary analysis of the German, Yiddish and Hebrew translations of The Merchant of Venice concludes that cultural context and political intentions changed dramatically between the two Hebrew translations in 1921 and 1972, limiting his textual analysis to the closing line of Shylock’s famous speech: ‘it shall go hard’. I examine two key words in that speech in the two translations to detect which biblical texts the translator called on, consciously or unconsciously, and gauge what the literary resources of the Hebrew language can make of Shylock and his complaint and whether the language portraying Shylock and his complaint did actually change over those fifty years.

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Hadari, Atar. "The Word of the Lord to Shylock." European Judaism 51, no. 2 (September 1, 2018): 83–90. http://dx.doi.org/10.3167/ej.2018.510213.

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Abstract Dror Abend-David’s Scorned My Nation in its comparative literary analysis of the German, Yiddish and Hebrew translations of The Merchant of Venice concludes that cultural context and political intentions changed dramatically between the two Hebrew translations in 1921 and 1972, limiting his textual analysis to the closing line of Shylock’s famous speech: ‘it shall go hard’. I examine two key words in that speech in the two translations to detect which biblical texts the translator called on, consciously or unconsciously, and gauge what the literary resources of the Hebrew language can make of Shylock and his complaint and whether the language portraying Shylock and his complaint did actually change over those fifty years.

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Dissertations / Theses on the topic "ÌÞesed (The Hebrew word)"

1

Goldfajn, Tal. "Word order and time in Biblical Hebrew narrative /." Oxford : Clarendon press, 1998. http://catalogue.bnf.fr/ark:/12148/cb37649978s.

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Boyd, Steven William. "The Use of ZAMAM and MEZIMMAH in Proverbs." Theological Research Exchange Network (TREN), 1985. http://www.tren.com.

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Unruh, Jeffrey R. ""Rule" and "subdue" in Genesis 1:26-28 and its implications for today." Theological Research Exchange Network (TREN), 1991. http://www.tren.com.

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Chen, Patrick Ta-Chi Yoon. "Rhetorical function of rûaḥ in Ezekiel 37:9-10." Online full text .pdf document, available to Fuller patrons only, 2003. http://www.tren.com.

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Simpson, Benjamin I. "Pesher in the New Testament." Theological Research Exchange Network (TREN), 2003. http://www.tren.com.

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6

Maloney, Leslie Don Bellinger W. H. "A word fitly spoken poetic artistry in the first four acrostics of the Hebrew psalter /." Waco, Tex. : Baylor University, 2005. http://hdl.handle.net/2104/3002.

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Musgrave, David. "The word shalom in the book of Isaiah." Theological Research Exchange Network (TREN), 1991. http://www.tren.com.

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8

Fowler, Robert Lee. "A theological word study of the root p̲q̲d̲." Theological Research Exchange Network (TREN), 1991. http://www.tren.com.

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Lunn, Nicholas P. Heimerdinger Jean-Marc. "Word-order variation in biblical Hebrew poetry : differentiating pragmatic poetics /." Carlisle : Paternoster press, 2006. http://catalogue.bnf.fr/ark:/12148/cb410779456.

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Wessner, Mark Daren. "Character evaluation in biblical Hebrew narrative toward a literary and theological understanding of the 'asher-verb formula /." Thesis, Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-02242010-152046/.

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Books on the topic "ÌÞesed (The Hebrew word)"

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1943-, Wikler Madeline, and Marzel Pepi, eds. My first Hebrew word book. Minneapolis: Kar-Ben Pub., 2005.

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2

The word Hesed in the Hebrew Bible. Sheffield: JSOT Press, 1993.

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3

Clark, Gordon R. The word 'hesed' in the Hebrew Bible. Sheffield: JSOT Press, 1993.

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4

Hebrew talk: 101 Hebrew roots and the stories they tell. Oakland, Calif: EKS Publishing, 2004.

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5

Revell, E. J. Nesiga (retraction of word stress) in Tiberian Hebrew. Madrid: Instituto de Filología, C.S.I.C., Departamento de Filología Bíblica y de Oriente Antiguo, 1987.

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6

Word order and time in Biblical Hebrew narrative. Oxford: Clarendon Press, 1998.

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7

Aphek, Edna. Word systems in modern Hebrew: Implications and applications. Leiden: E.J. Brill, 1988.

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8

Binyamini, Ariʼel Liʼat, ed. My Hebrew picture dictionary: The alef-bet word book. Brooklyn, N.Y: Mesorah Publications, 2001.

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9

Bolozky, Shmuel. Measuring productivity in word formation: The case of Israeli Hebrew. Leiden: Brill, 1999.

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10

Wrestling with the Word: Christian preaching from the Hebrew Bible. Valley Forge, Pa: Trinity Press International, 1996.

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Book chapters on the topic "ÌÞesed (The Hebrew word)"

1

Doron, Edit. "Word Order in Hebrew." In Research in Afroasiatic Grammar, 41–56. Amsterdam: John Benjamins Publishing Company, 2000. http://dx.doi.org/10.1075/cilt.202.03dor.

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2

Noegel, Scott B. "“Word Play” in Qoheleth." In Perspectives on Hebrew Scriptures IV, edited by Ehud Ben Zvi, 111–38. Piscataway, NJ, USA: Gorgias Press, 2008. http://dx.doi.org/10.31826/9781463216238-012.

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3

Ornan, Uzzi. "Machinery for Hebrew Word Formation." In Advances in Artificial Intelligence, 75–93. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-9052-7_4.

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4

Schwarzwald, Ora. "8. Opacity in Hebrew word morphology." In Language Processing and Acquisition in Languages of Semitic, Root-Based, Morphology, 147–63. Amsterdam: John Benjamins Publishing Company, 2003. http://dx.doi.org/10.1075/lald.28.08sch.

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HaCohen-Kerner, Yaakov, and Izek Greenfield. "Basic Word Completion and Prediction for Hebrew." In String Processing and Information Retrieval, 237–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34109-0_25.

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6

Linville, James R. "LETTING THE “BI-WORD” “RULE” IN JOEL 2:17." In Perspectives on Hebrew Scriptures II, 13–24. Piscataway, NJ, USA: Gorgias Press, 2007. http://dx.doi.org/10.31826/9781463212834-004.

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Shimron, Joseph. "Word Decomposition in Hebrew as a Semitic Language." In Reading Complex Words, 93–111. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-3720-2_5.

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8

Hawker, Nancy. "Arabic borrowing of the Hebrew word menahēl ‘manager’." In Arabic in Contact, 332–47. Amsterdam: John Benjamins Publishing Company, 2018. http://dx.doi.org/10.1075/sal.6.17haw.

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Berman, Ruth A. "Word class distinctiveness versus polycategoriality in Modern Hebrew." In Studies in Language Companion Series, 343–77. Amsterdam: John Benjamins Publishing Company, 2017. http://dx.doi.org/10.1075/slcs.182.12ber.

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Ben-David, Avivit, and Outi Bat-El. "Paths and stages in acquisition of the phonological word in Hebrew." In Acquisition and Development of Hebrew, 39–68. Amsterdam: John Benjamins Publishing Company, 2016. http://dx.doi.org/10.1075/tilar.19.02ben.

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Conference papers on the topic "ÌÞesed (The Hebrew word)"

1

Dinur, Elad, Dmitry Davidov, and Ari Rappoport. "Unsupervised concept discovery in Hebrew using simple unsupervised word prefix segmentation for Hebrew and Arabic." In the EACL 2009 Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1621774.1621782.

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2

"Emoji Identification and Prediction in Hebrew Political Corpus." In InSITE 2019: Informing Science + IT Education Conferences: Jerusalem. Informing Science Institute, 2019. http://dx.doi.org/10.28945/4346.

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[This Proceedings paper was revised and published in the 2019 issue of the journal Issues in Informing Science and Information Technology, Volume 16] Aim/Purpose: Any system that aims to address the task of modeling social media communication need to deal with the usage of emojis. Efficient prediction of the most likely emoji given the text of a message may help to improve different NLP tasks. Background: We explore two tasks: emoji identification and emoji prediction. While emoji prediction is a classification task of predicting the emojis that appear in a given text message, emoji identification is the complementary preceding task of determining if a given text message includes emojies. Methodology: We adopt a supervised Machine Learning (ML) approach. We compare two text representation approaches, i.e., n-grams and character n-grams and analyze the contribution of additional metadata features to the classification. Contribution: The task of emoji identification is novel. We extend the definition of the emoji prediction task by allowing to use not only the textual content but also meta-data analysis. Findings: Metadata improve the classification accuracy in the task of emoji identification. In the task of emoji prediction it is better to apply feature selection. Recommendations for Practitioners: In many of the cases the classifier decision seems fitter to the comment con-tent than the emoji that was chosen by the commentator. The classifier may be useful for emoji suggestion. Recommendations for Researchers: Explore character-based representations rather than word-based representations in the case of morphologically rich languages. Impact on Society: Improve the modeling of social media communication. Future Research: We plan to address the multi-label setting of the emoji prediction task and to investigate the deep learning approach for both of our classification tasks.

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