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@@ -22,10 +22,10 @@ At a high level, these are steps that were taken:
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  - Inserted translation notes and literal notes in place (preserving grammar and adding clarity to the corpus)
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  ## Credit
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- Credit for the aggregation of the raw data belongs to the [Akkademia](https://github.com/gaigutherz/Akkademia/tree/master) project. Specifically, the exact data file used as the starting dataset is linked [here](https://github.com/gaigutherz/Akkademia/blob/master/NMT_input/train.en) and was also used to train their SOTA neural machine translation Akkadian->English model as described in their recent [paper](https://academic.oup.com/pnasnexus/article/2/5/pgad096/7147349) Gutherz et. al 2023 [1].
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- Credit for the original source of the raw data belongs to the incredible Open Richly Annotated Cuneiform Corpus ([ORACC](http://oracc.museum.upenn.edu/)) project [2]. Specifically, as noted by the Akkademia project above, the RINAP 1, 3, 4, and 5 datasets are the source of the original raw data.
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  ## Citations
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  [1] Gai Gutherz, Shai Gordin, Luis Sáenz, Omer Levy, Jonathan Berant, Translating Akkadian to English with neural machine translation, PNAS Nexus, Volume 2, Issue 5, May 2023, pgad096, https://doi.org/10.1093/pnasnexus/pgad096
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- [2] Open Richly Annotated Cuneiform Corpus, http://oracc.org
 
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  - Inserted translation notes and literal notes in place (preserving grammar and adding clarity to the corpus)
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  ## Credit
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+ Credit for the aggregation of the raw data belongs to the [Akkademia](https://github.com/gaigutherz/Akkademia/tree/master) project. Specifically, the exact data file used as the starting dataset is linked [here](https://github.com/gaigutherz/Akkademia/blob/master/NMT_input/train.en) and was also used to train their SOTA neural machine translation Akkadian->English model as described in their recent [paper](https://academic.oup.com/pnasnexus/article/2/5/pgad096/7147349) Gutherz et al. 2023 [1].
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+ Credit for the original source of the raw data belongs to the incredible Open Richly Annotated Cuneiform Corpus ([ORACC](http://oracc.org)) project [2]. Specifically, as noted by the Akkademia project above, the RINAP 1, 3, 4, and 5 datasets are the source of the original raw data.
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  ## Citations
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  [1] Gai Gutherz, Shai Gordin, Luis Sáenz, Omer Levy, Jonathan Berant, Translating Akkadian to English with neural machine translation, PNAS Nexus, Volume 2, Issue 5, May 2023, pgad096, https://doi.org/10.1093/pnasnexus/pgad096
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+ [2] Jamie Novotny, Eleanor Robson, Steve Tinney, Niek Veldhuis, et al. Open Richly Annotated Cuneiform Corpus, http://oracc.org